Best AI tools for< Build Models >

ThirdAI is a production-ready AI platform designed for enterprises, offering a comprehensive solution for building AI applications without the need for extensive proof-of-concept cycles or manual fine-tuning. The platform provides enterprise-grade productivity tools, document search and retrieval, content creation, FAQ bots, customer live support, hyper-personalization, risk and compliance features, fraud detection, anomaly detection, and PII/sensitive data redaction. ThirdAI allows users to bring their business problems, apply them to data, and compose AI applications effortlessly. The platform supports no-code customization, turnkey deployment, and user engagement data for best-in-class accuracy.

Devv AI is an AI tool designed to provide developers with unlimited access to top models like GPT-4 and other advanced features. It serves as the next-Gen search engine for developers, allowing users to search the web, GitHub, and various tools. By upgrading to the Pro version, users can unlock advanced models, more search modes, and search history.

Aquarium is an AI tool that accelerates the process of building and deploying production AI systems. The platform has been instrumental in enhancing the capabilities of AI models, particularly in computer vision and natural language processing domains. By leveraging generative AI technology, Aquarium aims to bring value to a vast user base, spanning from college students to enterprises. The recent integration with Notion signifies a strategic move towards making AI more accessible and impactful in everyday life.

Streamlit is a web application framework that allows data scientists and machine learning engineers to create interactive web applications quickly and easily. It simplifies the process of building and sharing data-focused applications by providing a simple Python script that can be turned into a shareable web app with just a few lines of code. With Streamlit, users can create interactive visualizations, dashboards, and machine learning models without the need for web development expertise.

Scale AI is an AI tool that accelerates the development of AI applications for enterprise, government, and automotive sectors. It offers Scale Data Engine for generative AI, Scale GenAI Platform, and evaluation services for model developers. The platform leverages enterprise data to build sustainable AI programs and partners with leading AI models. Scale's focus on generative AI applications, data labeling, and model evaluation sets it apart in the AI industry.

HappyML is an AI tool designed to assist users in machine learning tasks. It provides a user-friendly interface for running machine learning algorithms without the need for complex coding. With HappyML, users can easily build, train, and deploy machine learning models for various applications. The tool offers a range of features such as data preprocessing, model evaluation, hyperparameter tuning, and model deployment. HappyML simplifies the machine learning process, making it accessible to users with varying levels of expertise.

Groq is a fast AI inference tool that offers instant intelligence for openly-available models like Llama 3.1. It provides ultra-low-latency inference for cloud deployments and is compatible with other providers like OpenAI. Groq's speed is proven to be instant through independent benchmarks, and it powers leading openly-available AI models such as Llama, Mixtral, Gemma, and Whisper. The tool has gained recognition in the industry for its high-speed inference compute capabilities and has received significant funding to challenge established players like Nvidia.

Novita AI is an AI cloud platform offering Model APIs, Serverless, and GPU Instance services in a cost-effective and integrated manner to accelerate AI businesses. It provides optimized models for high-quality dialogue use cases, full spectrum AI APIs for image, video, audio, and LLM applications, serverless auto-scaling based on demand, and customizable GPU solutions for complex AI tasks. The platform also includes a Startup Program, 24/7 service support, and has received positive feedback for its reasonable pricing and stable services.

Gradient Insight is a data science consulting and AI solutions provider. They offer a range of services including generative AI development, machine learning, computer vision, robotics and automation, AI strategy and roadmap, and data analytics. Their team of expert data scientists helps businesses to de-risk their investment in AI and to overcome barriers to engineering innovation. Gradient Insight has worked with clients such as Opitas, a fintech company, and the UK MOD. They offer a smooth and efficient process from consultation to delivery, and ongoing support and improvement.

Aify.co is a website that covers all things artificial intelligence. It provides news, analysis, and opinion on the latest developments in AI, as well as resources for developers and users. The site is written by a team of experts in AI, and it is committed to providing accurate and up-to-date information on the field.

MagicApps is a software company that specializes in AI and other technologies. They offer a variety of products, including AI-powered tools and applications.

Tredence is a data science and AI services company that provides end-to-end solutions for businesses across various industries. The company's services include data engineering, data analytics, AI consulting, and machine learning operations (MLOps). Tredence has a team of experienced data scientists and engineers who use their expertise to help businesses solve complex data challenges and achieve their business goals.

Superlinked is a compute framework for your information retrieval and feature engineering systems, focused on turning complex data into vector embeddings. Vectors power most of what you already do online - hailing a cab, finding a funny video, getting a date, scrolling through a feed or paying with a tap. And yet, building production systems powered by vectors is still too hard! Our goal is to help enterprises put vectors at the center of their data & compute infrastructure, to build smarter and more reliable software.

Built In is an online community for startups and tech companies. Find startup jobs, tech news and events.

Built In is an online community for startups and tech companies. Find startup jobs, tech news and events.

Kin + Carta is a global digital transformation consultancy that helps organizations embrace digital change through data, cloud, and experience design. The company's services include data and AI, cloud and platforms, experience and product design, managed services, and strategy and innovation. Kin + Carta has a team of over 2000 experts who work with clients in a variety of industries, including automotive, financial services, healthcare, and retail.

dbNix AI is an enterprise AI company that provides a range of AI-powered solutions for businesses. Their platform offers various services, including workspace automation, contact center automation, asset inventory management, database AI, digital persona sharing, lead management, human resource AI, and network monitoring. dbNix AI's mission is to provide customers with the most compelling AI solutions and deliver the highest quality of customer service.

VKTR is an online platform that provides resources and insights on the topic of artificial intelligence (AI) in the workplace. It offers articles, case studies, and other content to help users understand how AI is being used in various industries and roles, and how they can leverage AI to improve their own work.

TechCrunch is a leading technology media property, dedicated to obsessively profiling startups, reviewing new Internet products, and breaking tech news.

DagsHub is an open source data science collaboration platform that helps AI teams build better models and manage data projects. It provides a central location for data, code, experiments, and models, making it easy for teams to collaborate and track their progress. DagsHub also integrates with a variety of popular data science tools and frameworks, making it a powerful tool for data scientists and machine learning engineers.

MLflow is an open source platform for managing the end-to-end machine learning (ML) lifecycle, including tracking experiments, packaging models, deploying models, and managing model registries. It provides a unified platform for both traditional ML and generative AI applications.

Simplilearn is an online bootcamp and certification platform that offers courses in various fields, including AI and machine learning, project management, cyber security, cloud computing, and data science. The platform partners with leading universities and companies to provide industry-relevant training and certification programs. Simplilearn's courses are designed to help learners develop job-ready skills and advance their careers.

Datamation is a leading industry resource for B2B data professionals and technology buyers. Datamation’s focus is on providing insight into the latest trends and innovation in AI, data security, big data, and more, along with in-depth product recommendations and comparisons. More than 1.7M users gain insight and guidance from Datamation every year.

The Clark Center Forum is a repository of thoughtful, current, and reliable information regarding topics of the day, including artificial intelligence (AI). The website features articles, surveys, and polls on a variety of AI-related topics, such as the European Union's AI Act, the impact of AI on economic growth, and the use of AI in financial markets. The website also provides information on the Clark Center's Economic Experts Panels, which include experts on AI and other economic topics.

Towards Data Science is a Medium publication dedicated to sharing concepts, ideas, and codes in the field of data science. It provides a platform for data scientists, researchers, and practitioners to connect, learn, and contribute to the advancement of the field.

Latest AI Tools is an extensive directory of AI tools and GPT Store Apps, featuring over 1100 AI websites and tools. It serves as a comprehensive resource for individuals and businesses seeking to leverage the power of AI to enhance their productivity, streamline their workflows, and gain valuable insights.

ZDNet is a technology news website that provides news, reviews, and advice on the latest innovations in the tech industry. It covers a wide range of topics, including artificial intelligence, cloud computing, digital transformation, energy, robotics, sustainability, transportation, and work life. ZDNet's mission is to help readers understand the latest trends and developments in the tech industry and to make informed decisions about how to use technology to improve their lives and businesses.

Tableau Augmented Analytics is a class of analytics powered by artificial intelligence (AI) and machine learning (ML) that expands a human’s ability to interact with data at a contextual level. It uses AI to make analytics accessible so that more people can confidently explore and interact with data to drive meaningful decisions. From automated modeling to guided natural language queries, Tableau's augmented analytics capabilities are powerful and trusted to help organizations leverage their growing amount of data and empower a wider business audience to discover insights.

FranzAI LLM Playground is an AI-powered tool that helps you extract, classify, and analyze unstructured text data. It leverages transformer models to provide accurate and meaningful results, enabling you to build data applications faster and more efficiently. With FranzAI, you can accelerate product and content classification, enhance data interpretation, and advance data extraction processes, unlocking key insights from your textual data.

Nerdynav is a website that provides reviews of AI tools and software for businesses. The website is run by Nav, a software developer and online entrepreneur who has tested over 100 tools to help businesses find the best solutions for their needs. Nerdynav's reviews are data-backed and provide insights into the features, advantages, and disadvantages of each tool. The website also includes articles on how to use AI to improve business processes and increase productivity.

Coursera is an online learning platform that offers courses, specializations, and degrees from top universities and companies. It provides a wide range of subjects, including business, computer science, data science, and more. Coursera also offers a variety of learning formats, including self-paced courses, live online classes, and guided projects. With Coursera, you can learn at your own pace and on your own schedule.

AlphaCode is an AI-powered tool that helps businesses understand and leverage their data. It offers a range of services, including data vision, cloud, and product development. AlphaCode's AI capabilities enable it to analyze data, identify patterns, and make predictions, helping businesses make better decisions and achieve their goals.

Infrabase.ai is a directory of AI infrastructure products that helps users discover and explore a wide range of tools for building world-class AI products. The platform offers a comprehensive directory of products in categories such as Vector databases, Prompt engineering, Observability & Analytics, Inference APIs, Frameworks & Stacks, Fine-tuning, Audio, and Agents. Users can find tools for tasks like data storage, model development, performance monitoring, and more, making it a valuable resource for AI projects.

The Intel Gaudi AI accelerator developer website provides resources, guidance, tools, and support for building, migrating, and optimizing AI models. It offers software, model references, libraries, containers, and tools for training and deploying Generative AI and Large Language Models. The site focuses on the Intel Gaudi accelerators, including tutorials, documentation, and support for developers to enhance AI model performance.

Derwen is an open-source integration platform for production machine learning in enterprise, specializing in natural language processing, graph technologies, and decision support. It offers expertise in developing knowledge graph applications and domain-specific authoring. Derwen collaborates closely with Hugging Face and provides strong data privacy guarantees, low carbon footprint, and no cloud vendor involvement. The platform aims to empower AI engineers and domain experts with quality, time-to-value, and ownership since 2017.

ThoughtSpot is an AI-powered analytics platform that enables users to deliver insights 10x faster for their employees. It offers AI-powered search capabilities, natural language search, live querying of data, building search data models, balancing self-service with enterprise-scale control, visualizing business data, operationalizing data sync to business apps, and mobile access. The platform also provides features for creating visualizations from spreadsheets, staying up to date with product news, embedding analytics into apps, building ThoughtSpot apps and API services, and generating more revenue with embedded analytics. ThoughtSpot is designed to provide fast, actionable insights with a focus on user experience and self-service analytics.

Prem is an AI platform that empowers developers and businesses to build and fine-tune generative AI models with ease. It offers a user-friendly development platform for developers to create AI solutions effortlessly. For businesses, Prem provides tailored model fine-tuning and training to meet unique requirements, ensuring data sovereignty and ownership. Trusted by global companies, Prem accelerates the advent of sovereign generative AI by simplifying complex AI tasks and enabling full control over intellectual capital. With a suite of foundational open-source SLMs, Prem supercharges business applications with cutting-edge research and customization options.

GAIA is a powerful creation engine designed for the AI Age. It provides users with advanced tools and capabilities to develop AI applications, machine learning models, and data analytics solutions. With a user-friendly interface and robust features, GAIA empowers individuals and organizations to harness the potential of artificial intelligence for various projects and initiatives. Whether you are a data scientist, developer, or AI enthusiast, GAIA offers a comprehensive platform to bring your ideas to life and drive innovation in the rapidly evolving AI landscape.

Dale on AI is a website dedicated to providing insightful articles and guides on various topics related to artificial intelligence, machine learning, and deep learning. The website covers a wide range of subjects, from practical tutorials on building AI-powered applications to in-depth explanations of cutting-edge AI technologies. With a focus on making complex AI concepts accessible to developers and enthusiasts, Dale on AI serves as a valuable resource for anyone interested in exploring the world of artificial intelligence.

Techstrong.ai is an AI-focused website that covers a wide range of topics related to artificial intelligence, including AI at the Edge, AI Careers, Conversational AI, Cybersecurity AI, Data Engineering, Data Science, and more. The site provides the latest articles, news, videos, and related sites within the Techstrong Group. It offers insights into various industries such as Aerospace, Energy, Financial Services, Health Care, Retail, Telecommunications, and Transportation/Travel. Techstrong.ai aims to keep its audience informed about the latest developments and trends in the AI space.

Azure AI Platform by Microsoft offers a comprehensive suite of artificial intelligence services and tools for developers and businesses. It provides a unified platform for building, training, and deploying AI models, as well as integrating AI capabilities into applications. With a focus on generative AI, multimodal models, and large language models, Azure AI empowers users to create innovative AI-driven solutions across various industries. The platform also emphasizes content safety, scalability, and agility in managing AI projects, making it a valuable resource for organizations looking to leverage AI technologies.

Hopsworks is an AI platform that offers a comprehensive solution for building, deploying, and monitoring machine learning systems. It provides features such as a Feature Store, real-time ML capabilities, and generative AI solutions. Hopsworks enables users to develop and deploy reliable AI systems, orchestrate and monitor models, and personalize machine learning models with private data. The platform supports batch and real-time ML tasks, with the flexibility to deploy on-premises or in the cloud.

Tresata is an AI tool that offers inventory and cataloging, inferencing and connecting, discoverability and lineage tracking, tokenization, and data enrichment capabilities. It provides SAM (Smart Augmented Intelligence) features and seamless integrations for customers. The platform empowers users to create data products for AI applications by uploading data to the Tresata cloud and accessing it for analysis and insights. Tresata emphasizes the importance of good data for all, with a focus on data-driven decision-making and innovation.

madebymachines is an AI tool designed to assist users in various stages of the machine learning workflow, from data preparation to model development. The tool offers services such as data collection, data labeling, model training, hyperparameter tuning, and transfer learning. With a user-friendly interface and efficient algorithms, madebymachines aims to streamline the process of building machine learning models for both beginners and experienced users.

Tellius is an AI Augmented Analytics Software and Decision Intelligence platform that empowers users to get faster insights from data, break silos between Business Intelligence (BI) and AI, and accelerate complex data analysis with AI-driven automation. The platform offers guided insights, data preparation, natural language search, automated machine learning, and self-service analytics & reporting. Tellius is loved by analytics and business teams for providing instant ad hoc answers, simplifying complex analysis, and surfacing hidden key drivers and anomalies through best-in-class automated insights.

The website offers interactive tutorials on neural networks and deep learning, providing a comprehensive platform for mastering neural networks in an intuitive, natural, and cohesive manner. Users can access a visualized neural network lab with simplified datasets, a variety of 2D and 3D datasets for regression and classification, and interactive missions to deepen understanding. The platform also features intuitive tutorials, well-visualized neural network knowledge with charts and animations, and a visual deep learning model editor for efficient model building. Overall, it aims to enhance learning and understanding of neural networks through interactive and visual tools.

Plat.AI is an automated predictive analytics software that offers model building solutions for various industries such as finance, insurance, and marketing. It provides a real-time decision-making engine that allows users to build and maintain AI models without any coding experience. The platform offers features like automated model building, data preprocessing tools, codeless modeling, and personalized approach to data analysis. Plat.AI aims to make predictive analytics easy and accessible for users of all experience levels, ensuring transparency, security, and compliance in decision-making processes.

Deepnote is an AI-powered analytics and data science notebook platform designed for teams. It allows users to turn notebooks into powerful data apps and dashboards, combining Python, SQL, R, or even working without writing code at all. With Deepnote, users can query various data sources, generate code, explain code, and create interactive visualizations effortlessly. The platform offers features like collaborative workspaces, scheduling notebooks, deploying APIs, and integrating with popular data warehouses and databases. Deepnote prioritizes security and compliance, providing users with control over data access and encryption. It is loved by a community of data professionals and widely used in universities and by data analysts and scientists.

Domino Data Lab is an enterprise AI platform that enables users to build, deploy, and manage AI models across any environment. It fosters collaboration, establishes best practices, and ensures governance while reducing costs. The platform provides access to a broad ecosystem of open source and commercial tools, and infrastructure, allowing users to accelerate and scale AI impact. Domino serves as a central hub for AI operations and knowledge, offering integrated workflows, automation, and hybrid multicloud capabilities. It helps users optimize compute utilization, enforce compliance, and centralize knowledge across teams.

Data Science Dojo is a globally recognized e-learning platform that offers programs in data science, data analytics, machine learning, and more. They provide comprehensive and hands-on training in various formats such as in-person, virtual instructor-led, and self-paced training. The focus is on helping students develop a think-business-first mindset to apply their data science skills effectively in real-world scenarios. With over 2500 enterprises trained, Data Science Dojo aims to make data science accessible to everyone.

Strong Analytics is a data science consulting and machine learning engineering company that specializes in building bespoke data science, machine learning, and artificial intelligence solutions for various industries. They offer end-to-end services to design, engineer, and deploy custom AI products and solutions, leveraging a team of full-stack data scientists and engineers with cross-industry experience. Strong Analytics is known for its expertise in accelerating innovation, deploying state-of-the-art techniques, and empowering enterprises to unlock the transformative value of AI.

Fyne AI is an AI application that applies AI research in computer vision, generative AI, and machine learning to develop innovative products. The focus of the application is on automating analysis, generating insights from image and video datasets, enhancing creativity and productivity, and building prediction models. Users can subscribe to the Fyne AI newsletter to stay updated on product news and updates.

Open Data Science (ODS) is a community website offering a platform for data science enthusiasts to engage in tracks, competitions, hacks, tasks, events, and projects. The website serves as a hub for job opportunities and provides a space for privacy policy, service agreements, and public offers. ODS.AI, established in 2015, focuses on various data science topics such as machine learning, computer vision, natural language processing, and more. The platform hosts online and offline events, conferences, and educational courses to foster learning and networking within the data science community.

nventr is an AI platform for predictive automation, offering a suite of products and services powered by predictive analytics. The company focuses on applying new approaches to uncover patterns, extract valuable intelligence, and predict outcomes within vast datasets. nventr solutions support enterprise-grade AI acceleration, intelligent data processing, and digital transformation. The platform, nventr.ai, enables rapid building of AI models and software applications through collaborative tools and cloud-based infrastructure.

Bay Area AI is a technical AI meetup group based in San Francisco, CA, consisting of startup engineers, research scientists, computational linguists, mathematicians, and philosophers. The group focuses on understanding the meaning of text, reasoning, and human intent through technology to build new businesses and enhance the human experience in the modern connected world. They work on building systems with Machine Learning on top of Data Pipelines, exploring open-source solutions, and modeling human behavior in industry for practical results.

Every AI is an AI software that offers over 120 AI models, including ChatGPT from OpenAI and Anthropic/Claude, for a wide range of applications. It provides incredible speeds and access to all models for a subscription fee of $20. The platform aims to simplify AI development at scale by offering developer-friendly solutions with extensive documentation and SDKs for popular programming languages like Ruby and JavaScript.

ThoughtSpot is an AI-powered analytics platform that enables users to deliver insights 10x faster for their employees. It offers AI-powered search capabilities, natural language search, live-querying of data, building search data models, balancing self-service with enterprise-scale control, visualizing business data with Liveboards, surfacing actionable insights with augmented analytics, operationalizing cloud data sync, and more. ThoughtSpot aims to provide fast, actionable insights for all users, eliminating reporting backlogs and developer headaches.

The Cerebras API is a high-speed inferencing solution for AI model inference powered by Cerebras Wafer-Scale Engines and CS-3 systems. It offers developers access to two models: Meta’s Llama 3.1 8B and 70B models, which are instruction-tuned and suitable for conversational applications. The API provides low-latency solutions and invites developers to explore new possibilities in AI development.

SentiSight.ai is a machine learning platform for image recognition solutions, offering services such as object detection, image segmentation, image classification, image similarity search, image annotation, computer vision consulting, and intelligent automation consulting. Users can access pre-trained models, background removal, NSFW detection, text recognition, and image recognition API. The platform provides tools for image labeling, project management, and training tutorials for various image recognition models. SentiSight.ai aims to streamline the image annotation process, empower users to build and train their own models, and deploy them for online or offline use.

Tecton is an AI data platform that helps build smarter AI applications by simplifying feature engineering, generating training data, serving real-time data, and enhancing AI models with context-rich prompts. It automates data pipelines, improves model accuracy, and lowers production costs, enabling faster deployment of AI models. Tecton abstracts away data complexity, provides a developer-friendly experience, and allows users to create features from any source. Trusted by top engineering teams, Tecton streamlines ML delivery processes, improves customer interactions, and automates release processes through CI/CD pipelines.

Sorrentum is an open-source project that aims to combine open-source development, startups, and brilliant students to build machine learning, AI, and Web3 / DeFi protocols geared towards finance and economics. The project provides opportunities for internships, research assistantships, and development grants, as well as the chance to work on cutting-edge problems, learn about startups, write academic papers, and get internships and full-time positions at companies working on Sorrentum applications.

Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. It is designed to be easy to get started with and simple to use for Java developers. DJL provides a native Java development experience and allows users to integrate machine learning and deep learning models with their Java applications. The framework is deep learning engine agnostic, enabling users to switch engines at any point for optimal performance. DJL's ergonomic API interface guides users with best practices to accomplish deep learning tasks, such as running inference and training neural networks.

Craftgen.ai is an innovative AI platform designed for both technical and non-technical users. It's built on a foundation of graph architecture for scalability and the Actor Model for efficient concurrent operations, tailored to both technical and non-technical users. A key aspect of Craftgen.ai is its modular AI approach, allowing users to assemble and customize AI components like building blocks to fit their specific needs. The platform's robustness is enhanced by its event-driven architecture, ensuring reliable data processing and featuring browser web technologies for universal access. Craftgen.ai excels in dynamic tool and workflow generation, with strong offline capabilities for secure environments and plans for desktop application integration. A unique and valuable feature of Craftgen.ai is its marketplace, where users can access a variety of pre-built AI solutions. This marketplace accelerates the deployment of AI tools but also fosters a community of sharing and innovation. Users can contribute to and leverage this repository of solutions, enhancing the platform's versatility and practicality. Craftgen.ai uses JSON schema for industry-standard alignment, enabling seamless integration with any API following the OpenAPI spec. This allows for a broad range of applications, from automating data analysis to streamlining content management. The platform is designed to bridge the gap between advanced AI technology and practical usability. It's a flexible, secure, and intuitive platform that empowers users, from developers seeking to create custom AI solutions to businesses looking to automate routine tasks. Craftgen.ai's goal is to make AI technology an integral, seamless part of everyday problem-solving and innovation, providing a platform where modular AI and a thriving marketplace converge to meet the diverse needs of its users.

This repository contains a collection of resources in the form of eBooks related to Data Science, Machine Learning, and similar topics.

BambooAI is a lightweight library utilizing Large Language Models (LLMs) to provide natural language interaction capabilities, much like a research and data analysis assistant enabling conversation with your data. You can either provide your own data sets, or allow the library to locate and fetch data for you. It supports Internet searches and external API interactions.

This repository provides a comprehensive collection of resources, open-source tools, and knowledge related to quantitative analysis. It serves as a valuable knowledge base and navigation guide for individuals interested in various aspects of quantitative investing, including platforms, programming languages, mathematical foundations, machine learning, deep learning, and practical applications. The repository is well-structured and organized, with clear sections covering different topics. It includes resources on system platforms, programming codes, mathematical foundations, algorithm principles, machine learning, deep learning, reinforcement learning, graph networks, model deployment, and practical applications. Additionally, there are dedicated sections on quantitative trading and investment, as well as large models. The repository is actively maintained and updated, ensuring that users have access to the latest information and resources.

A massive list including a huge amount of products and services that are completely free! ⭐ Star on GitHub • 🤝 Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL

This repository contains materials for the Microsoft Learn AI Fundamentals module. It covers the basics of artificial intelligence, machine learning, and data science. The content includes hands-on labs, interactive learning modules, and assessments to help learners understand key concepts and techniques in AI. Whether you are new to AI or looking to expand your knowledge, this module provides a comprehensive introduction to the fundamentals of AI.

The Java-AI-Book-Code repository contains code examples for the 2020 edition of 'Practical Artificial Intelligence With Java'. It is a comprehensive update of the previous 2013 edition, featuring new content on deep learning, knowledge graphs, anomaly detection, linked data, genetic algorithms, search algorithms, and more. The repository serves as a valuable resource for Java developers interested in AI applications and provides practical implementations of various AI techniques and algorithms.

The 'ai-demos' repository is a collection of example code from presentations focusing on building with AI and LLMs. It serves as a resource for developers looking to explore practical applications of artificial intelligence in their projects. The code snippets showcase various techniques and approaches to leverage AI technologies effectively. The repository aims to inspire and educate developers on integrating AI solutions into their applications.

CrewAI quickstart is a small project providing starter templates for an easy start with CrewAI. It includes notebooks, Python scripts, GUI with Streamlit, and Local LLMs for various tasks like web search, CSV lookup, web scraping, PDF search, and more. Contributions are welcome to enhance the project.

Ollama4j is a Java library that serves as a wrapper or binding for the Ollama server. It facilitates communication with the Ollama server and provides models for deployment. The tool requires Java 11 or higher and can be installed locally or via Docker. Users can integrate Ollama4j into Maven projects by adding the specified dependency. The tool offers API specifications and supports various development tasks such as building, running unit tests, and integration tests. Releases are automated through GitHub Actions CI workflow. Areas of improvement include adhering to Java naming conventions, updating deprecated code, implementing logging, using lombok, and enhancing request body creation. Contributions to the project are encouraged, whether reporting bugs, suggesting enhancements, or contributing code.

Jupyter Quant is a dockerized environment tailored for quantitative research, equipped with essential tools like statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, numpy, pandas, sci-py, scikit-learn, yellowbricks, shap, optuna, ib_insync, Cython, Numba, bottleneck, numexpr, jedi language server, jupyterlab-lsp, black, isort, and more. It does not include conda/mamba and relies on pip for package installation. The image is optimized for size, includes common command line utilities, supports apt cache, and allows for the installation of additional packages. It is designed for ephemeral containers, ensuring data persistence, and offers volumes for data, configuration, and notebooks. Common tasks include setting up the server, managing configurations, setting passwords, listing installed packages, passing parameters to jupyter-lab, running commands in the container, building wheels outside the container, installing dotfiles and SSH keys, and creating SSH tunnels.

libLLM is an open-source project designed for efficient inference of large language models (LLM) on personal computers and mobile devices. It is optimized to run smoothly on common devices, written in C++14 without external dependencies, and supports CUDA for accelerated inference. Users can build the tool for CPU only or with CUDA support, and run libLLM from the command line. Additionally, there are API examples available for Python and the tool can export Huggingface models.

The Data Scientist Roadmap2024 provides a comprehensive guide to mastering essential tools for data science success. It includes programming languages, machine learning libraries, cloud platforms, and concepts categorized by difficulty. The roadmap covers a wide range of topics from programming languages to machine learning techniques, data visualization tools, and DevOps/MLOps tools. It also includes web development frameworks and specific concepts like supervised and unsupervised learning, NLP, deep learning, reinforcement learning, and statistics. Additionally, it delves into DevOps tools like Airflow and MLFlow, data visualization tools like Tableau and Matplotlib, and other topics such as ETL processes, optimization algorithms, and financial modeling.

This repository contains recipes for building and running containerized AI and LLM applications with Podman. It provides model servers that serve machine-learning models via an API, allowing developers to quickly prototype new AI applications locally. The recipes include components like model servers and AI applications for tasks such as chat, summarization, object detection, etc. Images for sample applications and models are available in `quay.io`, and bootable containers for AI training on Linux OS are enabled.

LLMOps Workshop is a course designed to help users build, evaluate, monitor, and deploy Large Language Model solutions efficiently using Azure AI, Azure Machine Learning Prompt Flow, Content Safety, and Azure OpenAI. The workshop covers various aspects of LLMOps to help users master the process.

Community plugins repository for Google Firebase Genkit, containing various plugins for AI APIs and Vector Stores. Developed by The Fire Company, this repository offers plugins like genkitx-anthropic, genkitx-cohere, genkitx-groq, genkitx-mistral, genkitx-openai, genkitx-convex, and genkitx-hnsw. Users can easily install and use these plugins in their projects, with examples provided in the documentation. The repository also showcases products like Fireview and Giftit built using these plugins, and welcomes contributions from the community.

This repository contains slides, notebooks, and data for the Machine Learning University (MLU) Responsible AI class. The mission is to make Machine Learning accessible to everyone, covering widely used ML techniques and applying them to real-world problems. The class includes lectures, final projects, and interactive visuals to help users learn about Responsible AI and core ML concepts.

This repository is a collection of references to Azure OpenAI, Large Language Models (LLM), and related services and libraries. It provides information on various topics such as RAG, Azure OpenAI, LLM applications, agent design patterns, semantic kernel, prompting, finetuning, challenges & abilities, LLM landscape, surveys & references, AI tools & extensions, datasets, and evaluations. The content covers a wide range of topics related to AI, machine learning, and natural language processing, offering insights into the latest advancements in the field.

ABigSurveyOfLLMs is a repository that compiles surveys on Large Language Models (LLMs) to provide a comprehensive overview of the field. It includes surveys on various aspects of LLMs such as transformers, alignment, prompt learning, data management, evaluation, societal issues, safety, misinformation, attributes of LLMs, efficient LLMs, learning methods for LLMs, multimodal LLMs, knowledge-based LLMs, extension of LLMs, LLMs applications, and more. The repository aims to help individuals quickly understand the advancements and challenges in the field of LLMs through a collection of recent surveys and research papers.

The mslearn-knowledge-mining repository contains lab files for Azure AI Knowledge Mining modules. It provides resources for learning and implementing knowledge mining techniques using Azure AI services. The repository is designed to help users explore and understand how to leverage AI for knowledge mining purposes within the Azure ecosystem.

Jupyter Quant is a dockerized environment tailored for quantitative research, equipped with essential tools like statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, numpy, pandas, sci-py, scikit-learn, yellowbricks, shap, optuna, and more. It provides Interactive Broker connectivity via ib_async and includes major Python packages for statistical and time series analysis. The image is optimized for size, includes jedi language server, jupyterlab-lsp, and common command line utilities. Users can install new packages with sudo, leverage apt cache, and bring their own dot files and SSH keys. The tool is designed for ephemeral containers, ensuring data persistence and flexibility for quantitative analysis tasks.

This repository contains a demo application showcasing the usage of the SDXL Lightning API by fal.ai. The application also demonstrates the functionality of the fal.realtime client. To get started, users need to have a Fal AI API key for model access. The setup involves adding the API key to the .env.local file, installing dependencies using 'npm install', and running the application with 'npm run dev'.

A drill of scientific methods, processes, algorithms, and systems to build stories & models. An in-depth learning resource for humans. This repository is designed for individuals aiming to excel in the field of Data and AI, providing video sessions and text content for learning. It caters to those in leadership positions, professionals, and students, emphasizing the need for dedicated effort to achieve excellence in the tech field. The content covers various topics with a focus on practical application.

rLLM (relationLLM) is a Pytorch library for Relational Table Learning (RTL) with LLMs. It breaks down state-of-the-art GNNs, LLMs, and TNNs as standardized modules and facilitates novel model building in a 'combine, align, and co-train' way using these modules. The library is LLM-friendly, processes various graphs as multiple tables linked by foreign keys, introduces new relational table datasets, and is supported by students and teachers from Shanghai Jiao Tong University and Tsinghua University.

Neuromatch Academy NeuroAI Course Syllabus is a repository that contains the schedule and licensing information for the NeuroAI course. The course is designed to provide participants with a comprehensive understanding of artificial intelligence in neuroscience. It covers various topics related to AI applications in neuroscience, including machine learning, data analysis, and computational modeling. The content is primarily accessed from the ebook provided in the repository, and the course is scheduled for July 15-26, 2024. The repository is shared under a Creative Commons Attribution 4.0 International License and software elements are additionally licensed under the BSD (3-Clause) License. Contributors to the project are acknowledged and welcomed to contribute further.

mlcourse.ai is an open Machine Learning course by OpenDataScience (ods.ai), led by Yury Kashnitsky (yorko). The course offers a perfect balance between theory and practice, with math formulae in lectures and practical assignments including Kaggle Inclass competitions. It is currently in a self-paced mode, guiding users through 10 weeks of content covering topics from Pandas to Gradient Boosting. The course provides articles, lectures, and assignments to enhance understanding and application of machine learning concepts.

DataHorse is an open-source tool and Python library that simplifies data science for everyone. It allows users to interact with data in plain English without requiring technical skills. Users can create graphs, modify data, and build machine learning models to make predictions. The tool is designed to help businesses and individuals quickly understand their data and make data-driven decisions with ease.

Awesome AI & Data GitHub-Repos is a curated list of essential GitHub repositories covering the AI & ML landscape. It includes resources for Natural Language Processing, Large Language Models, Computer Vision, Data Science, Machine Learning, MLOps, Data Engineering, SQL & Database, and Statistics. The repository aims to provide a comprehensive collection of projects and resources for individuals studying or working in the field of AI and data science.

This repository serves as an educational resource for pharmaceutical and chemistry students to learn the basics of Deep Learning through a collection of Jupyter Notebooks. The content covers various topics such as Introduction to Jupyter, Python, Cheminformatics & RDKit, Linear Regression, Data Science, Linear Algebra, Neural Networks, PyTorch, Convolutional Neural Networks, Transfer Learning, Recurrent Neural Networks, Autoencoders, Graph Neural Networks, and Summary. The notebooks aim to provide theoretical concepts to understand neural networks through code completion, but instructors are encouraged to supplement with their own lectures. The work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Sail is a tool designed to unify stream processing, batch processing, and compute-intensive workloads, serving as a drop-in replacement for Spark SQL and the Spark DataFrame API in single-process settings. It aims to streamline data processing tasks and facilitate AI workloads.

INFO8006 Introduction to Artificial Intelligence is a course at ULiège that covers various topics in AI such as intelligent agents, problem-solving, games, probabilistic reasoning, machine learning, neural networks, reinforcement learning, and decision-making. The course includes lectures, exercises, and programming projects using Python. Students can access course materials, previous exams, and archived lectures to enhance their understanding of AI concepts.

Pixeltable is a Python library designed for ML Engineers and Data Scientists to focus on exploration, modeling, and app development without the need to handle data plumbing. It provides a declarative interface for working with text, images, embeddings, and video, enabling users to store, transform, index, and iterate on data within a single table interface. Pixeltable is persistent, acting as a database unlike in-memory Python libraries such as Pandas. It offers features like data storage and versioning, combined data and model lineage, indexing, orchestration of multimodal workloads, incremental updates, and automatic production-ready code generation. The tool emphasizes transparency, reproducibility, cost-saving through incremental data changes, and seamless integration with existing Python code and libraries.

CS7320-AI is a repository containing lecture materials, simple Python code examples, and assignments for the course CS 5/7320 Artificial Intelligence. The code examples cover various chapters of the textbook 'Artificial Intelligence: A Modern Approach' by Russell and Norvig. The repository focuses on basic AI concepts rather than advanced implementation techniques. It includes HOWTO guides for installing Python, working on assignments, and using AI with Python.

Recommenders is a project under the Linux Foundation of AI and Data that assists researchers, developers, and enthusiasts in prototyping, experimenting with, and bringing to production a range of classic and state-of-the-art recommendation systems. The repository contains examples and best practices for building recommendation systems, provided as Jupyter notebooks. It covers tasks such as preparing data, building models using various recommendation algorithms, evaluating algorithms, tuning hyperparameters, and operationalizing models in a production environment on Azure. The project provides utilities to support common tasks like loading datasets, evaluating model outputs, and splitting training/test data. It includes implementations of state-of-the-art algorithms for self-study and customization in applications.

JAX AI Stack is a suite of libraries built around the JAX Python package for array-oriented computation and program transformation. It provides a growing ecosystem of packages for specialized numerical computing across various domains, encouraging modularity and innovation in domain-specific libraries. The stack includes core packages like JAX, flax for building neural networks, ml_dtypes for NumPy dtype extensions, optax for gradient processing and optimization, and orbax for checkpointing and persistence utilities. Optional packages like grain data loader and tensorflow are also available for installation.

PythonDataScienceFullThrottle is a comprehensive repository containing various Python scripts, libraries, and tools for data science enthusiasts. It includes a wide range of functionalities such as data preprocessing, visualization, machine learning algorithms, and statistical analysis. The repository aims to provide a one-stop solution for individuals looking to dive deep into the world of data science using Python.

Auto-Analyst is an AI-driven data analytics agentic system designed to simplify and enhance the data science process. By integrating various specialized AI agents, this tool aims to make complex data analysis tasks more accessible and efficient for data analysts and scientists. Auto-Analyst provides a streamlined approach to data preprocessing, statistical analysis, machine learning, and visualization, all within an interactive Streamlit interface. It offers plug and play Streamlit UI, agents with data science speciality, complete automation, LLM agnostic operation, and is built using lightweight frameworks.

Daily-DeepLearning is a repository that covers various computer science topics such as data structures, operating systems, computer networks, Python programming, data science packages like numpy, pandas, matplotlib, machine learning theories, deep learning theories, NLP concepts, machine learning practical applications, deep learning practical applications, and big data technologies like Hadoop and Hive. It also includes coding exercises related to '剑指offer'. The repository provides detailed explanations and examples for each topic, making it a comprehensive resource for learning and practicing different aspects of computer science and data-related fields.

Sanic-Web is a lightweight, end-to-end, and easily customizable large model application project built on technologies such as Dify, Ollama & Vllm, Sanic, and Text2SQL. It provides a one-stop solution for developing large model applications, supporting graphical data-driven Q&A using ECharts, handling table-based Q&A with CSV files, and integrating with third-party RAG systems for general knowledge Q&A. As a lightweight framework, Sanic-Web enables rapid iteration and extension to facilitate the quick implementation of large model projects.

The AI Data Science Team of Copilots is an AI-powered data science team that uses agents to help users perform common data science tasks 10X faster. It includes agents specializing in data cleaning, preparation, feature engineering, modeling, and interpretation of business problems. The project is a work in progress with new data science agents to be released soon. Disclaimer: This project is for educational purposes only and not intended to replace a company's data science team. No warranties or guarantees are provided, and the creator assumes no liability for financial loss.

This repository is a collection of notes and knowledge based on the 'AI and Machine Learning for Coders' book, presented in Vietnamese. It includes additional explanations, code snippets, and illustrations to aid understanding. The content is a combination of the book's teachings and the author's personal experiences, tailored to help beginners grasp the operational aspects and results of computations easily.

A drill of scientific methods, processes, algorithms, and systems to build stories & models. An in-depth learning resource for humans. This is a drill for people who aim to be in the top 1% of Data and AI experts. The repository provides a routine for deep and shallow work sessions, covering topics from Python to AI/ML System Design and Personal Branding & Portfolio. It emphasizes the importance of continuous effort and action in the tech field.

The AI Tutor RAG System repository contains Jupyter notebooks supporting the RAG course, focusing on enhancing AI models with retrieval-based methods. It covers foundational and advanced concepts in retrieval-augmented generation, including data retrieval techniques, model integration with retrieval systems, and practical applications of RAG in real-world scenarios.

This Github repository contains practice session materials for the TUM course on Artificial Intelligence in Automotive Technology. It includes coding examples used in the lectures to teach the foundations of AI in automotive technology. The repository aims to provide hands-on experience and practical knowledge in applying AI concepts to the automotive industry.

LlamaV-o1 is a Large Multimodal Model designed for spontaneous reasoning tasks. It outperforms various existing models on multimodal reasoning benchmarks. The project includes a Step-by-Step Visual Reasoning Benchmark, a novel evaluation metric, and a combined Multi-Step Curriculum Learning and Beam Search Approach. The model achieves superior performance in complex multi-step visual reasoning tasks in terms of accuracy and efficiency.

This repository contains examples showcasing various uses of Spring AI Alibaba, from basic to advanced, and best practices for AI projects. It welcomes contributions related to Spring AI Alibaba usage examples, API usage, Spring AI usage examples, and best practices for AI projects. The project structure is designed to modularize functions for easy access and use.

The Llama Cookbook is the official guide for building with Llama Models, providing resources for inference, fine-tuning, and end-to-end use-cases of Llama Text and Vision models. The repository includes popular community approaches, use-cases, and recipes for working with Llama models. It covers topics such as multimodal inference, inferencing using Llama Guard, and specific tasks like Email Agent and Text to SQL. The structure includes sections for 3P Integrations, End to End Use Cases, Getting Started guides, and the source code for the original llama-recipes library.

This repository is a curated collection of data science and AI concepts and IQs, covering topics from foundational mathematics to cutting-edge generative AI concepts. It aims to support learners and professionals preparing for various data science roles by providing detailed explanations and notebooks for each concept.

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Expert guide on VASP, including online references

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Object Messaging and Intelligent Object Model for Deep AI integration with software

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