Best AI tools for< Build Learning Ecosystems >
20 - AI tool Sites
SweetRush
SweetRush is a corporate training and eLearning company that provides custom learning solutions, talent solutions, XR immersive tech for learning, voiceover services, and support for nonprofits. They specialize in creating engaging and effective learning programs that help businesses thrive. SweetRush has been recognized for its excellence in learning and development, winning numerous awards for its innovative and impactful work.
Duckietown
Duckietown is a platform for delivering cutting-edge robotics and AI learning experiences. It offers teaching resources to instructors, hands-on activities to learners, an accessible research platform to researchers, and a state-of-the-art ecosystem for professional training. Duckietown's mission is to make robotics and AI education state-of-the-art, hands-on, and accessible to all.
TensorFlow
TensorFlow is an end-to-end platform for machine learning. It provides a wide range of tools and resources to help developers build, train, and deploy ML models. TensorFlow is used by researchers and developers all over the world to solve real-world problems in a variety of domains, including computer vision, natural language processing, and robotics.
Apache MXNet
Apache MXNet is a flexible and efficient deep learning library designed for research, prototyping, and production. It features a hybrid front-end that seamlessly transitions between imperative and symbolic modes, enabling both flexibility and speed. MXNet also supports distributed training and performance optimization through Parameter Server and Horovod. With bindings for multiple languages, including Python, Scala, Julia, Clojure, Java, C++, R, and Perl, MXNet offers wide accessibility. Additionally, it boasts a thriving ecosystem of tools and libraries that extend its capabilities in computer vision, NLP, time series, and more.
Indie Hackers
Indie Hackers is an online community platform where entrepreneurs, startup founders, and indie hackers come together to share ideas, stories, and products related to building profitable online businesses. The platform offers a space for collaboration, networking, and learning from successful individuals in the startup ecosystem. Users can engage in discussions, seek feedback, and showcase their projects to a supportive community of like-minded individuals.
ALL IN
ALL IN is a premier event dedicated to the Canadian AI ecosystem, aiming to support the artificial intelligence industry in building an AI-powered economy. The event brings together AI enthusiasts, industry leaders, and experts to share insights, practical use cases, and foster collaboration. With over 200 distinguished speakers, ALL IN provides a platform for decision-makers to explore innovative solutions, exchange ideas, and forge partnerships to thrive in an AI-driven economy.
Domino Data Lab
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.
MarsX
MarsX is a revolutionary dev tool that seamlessly integrates AI, NoCode, Code, and MicroApps, empowering developers to create innovative software solutions with unprecedented speed and efficiency. At its core, MarsX offers a comprehensive suite of features that cater to the diverse needs of developers, from AI-powered landing page builders to a vast Micro AppStore brimming with ready-to-use Micro-Apps. These Micro-Apps, meticulously crafted by developers worldwide, provide instant access to a plethora of functionalities, enabling developers to rapidly assemble complex applications without the need for extensive coding. MarsX's commitment to innovation extends beyond its core offerings, as evidenced by its continuous development of cutting-edge tools such as AI website builders and AI-powered UI generators. These tools leverage the transformative power of AI to streamline the development process, allowing developers to focus on their creativity and strategic decision-making. By harnessing the collective knowledge and expertise of a global developer community, MarsX fosters a collaborative environment where developers can share their creations, learn from each other, and contribute to the ever-expanding ecosystem of Micro-Apps. MarsX's mission is to democratize software development, making it accessible to individuals and teams of all skill levels. With its intuitive interface, comprehensive documentation, and a supportive community, MarsX empowers developers to bring their ideas to life, transforming complex software development into an accessible and enjoyable experience.
SingularityNET
SingularityNET is a decentralized AI platform that offers funding opportunities for AI projects. It allows individuals and organizations to develop and monetize their AI services while keeping ownership of their models. The platform aims to build a global ecosystem of decentralized and beneficial AI services through community-driven programs and rewards. SingularityNET provides a space for project proposals, expert reviews, and grants to support the growth of AI projects aligned with the goal of building a Beneficial Artificial General Intelligence.
Disprz
Disprz is a Skills & Learning Platform designed to accelerate onboarding, job readiness, career mobility, and upskilling/reskilling to address talent gaps. It offers AI-driven personalized skilling, mobile-first frontline enablement, feature-rich mobile learning, decision support dashboard & analytics, and a marketplace ecosystem. The platform simplifies skills and roles, provides market intelligence on trending skills, and helps in identifying critical skills aligned with business strategy. It enables personalized learning experiences, career growth opportunities, leadership talent pipeline creation, and data-driven decision-making for learning investments.
Kira Systems
Kira Systems is a machine learning contract search, review, and analysis software that helps businesses identify, extract, and analyze content in their contracts and documents. It uses patented machine learning technology to extract concepts and data points with high efficiency and accuracy. Kira also has built-in intelligence that streamlines the contract review process with out-of-the-box smart fields. Businesses can also create their own smart fields to find specific data points using Kira's no-code machine learning tool. Kira's adaptive workflows allow businesses to organize, track, and export results. Kira has a partner ecosystem that allows businesses to transform how teams work with their contracts.
Lily AI
Lily AI is an e-commerce product discovery platform that helps brands increase sales and improve customer experience. It uses artificial intelligence to understand the language of customers and inject it across the retail ecosystem, from search to recommendations to demand forecasting. Lily AI's platform is purpose-built for retail and turns qualitative product attributes into a universal, customer-centered mathematical language with unprecedented accuracy. This results in a depth and scale of attribution that no other solution can match.
Practical Deep Learning for Coders
Practical Deep Learning for Coders is a free course designed for individuals with some coding experience who want to learn how to apply deep learning and machine learning to practical problems. The course covers topics such as building and training deep learning models for computer vision, natural language processing, tabular analysis, and collaborative filtering problems. It is based on a 5-star rated book and does not require any special hardware or software. The course is led by Jeremy Howard, a renowned expert in machine learning and the President and Chief Scientist of Kaggle.
DagsHub
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.
Wonda
Wonda is an AI-powered platform that enables users to create immersive learning experiences and simulations. It offers a range of features such as AI companions, quiz and assessments, virtual tours, role-playing games, and virtual workshops. Users can easily build interactive learning journeys without the need for coding. Wonda aims to enhance engagement and collaboration in training and onboarding processes, making learning experiences unforgettable and impactful. The platform supports integration with various learning management systems and provides advanced role management options for secure sharing. With Wonda, users can unleash their creativity and build virtual exhibits to showcase their ideas and projects in a fun and engaging way.
scikit-learn
Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.
KDnuggets
KDnuggets is a leading online resource for data science, machine learning, artificial intelligence, and analytics. The website provides a wealth of information on these topics, including articles, tutorials, interviews, and resources. KDnuggets also hosts a number of online communities and forums where users can connect with each other and share knowledge.
Numerai
Numerai is a data science tournament platform where users can compete to build models that predict the stock market. The platform provides users with clean and regularized hedge fund quality data, and users can build models using Python or R scripts. Numerai also has a cryptocurrency, NMR, which users can stake on their models to earn rewards.
ConsciousML
ConsciousML is a blog that provides in-depth and beginner-friendly content on machine learning, data engineering, and productivity. The blog covers a wide range of topics, including ML model deployment, data pipelines, deep work, data engineering, and more. The articles are written by experts in the field and are designed to help readers learn about the latest trends and best practices in machine learning and data engineering.
Analytics India Magazine
Analytics India Magazine is a leading publication covering the latest advancements in artificial intelligence, data science, and machine learning. The website provides in-depth analysis, interviews with industry experts, and insights into the impact of AI on various sectors. It also hosts events and conferences that bring together professionals and thought leaders in the field.
20 - Open Source AI Tools
SynapseML
SynapseML (previously known as MMLSpark) is an open-source library that simplifies the creation of massively scalable machine learning (ML) pipelines. It provides simple, composable, and distributed APIs for various machine learning tasks such as text analytics, vision, anomaly detection, and more. Built on Apache Spark, SynapseML allows seamless integration of models into existing workflows. It supports training and evaluation on single-node, multi-node, and resizable clusters, enabling scalability without resource wastage. Compatible with Python, R, Scala, Java, and .NET, SynapseML abstracts over different data sources for easy experimentation. Requires Scala 2.12, Spark 3.4+, and Python 3.8+.
awesome-algorand
Awesome Algorand is a curated list of resources related to the Algorand Blockchain, including official resources, wallets, blockchain explorers, portfolio trackers, learning resources, development tools, DeFi platforms, nodes & consensus participation, subscription management, security auditing services, blockchain bridges, oracles, name services, community resources, Algorand Request for Comments, metrics and analytics services, decentralized voting tools, and NFT marketplaces. The repository provides a comprehensive collection of tools, tutorials, protocols, and platforms for developers, users, and enthusiasts interested in the Algorand ecosystem.
web-llm
WebLLM is a modular and customizable javascript package that directly brings language model chats directly onto web browsers with hardware acceleration. Everything runs inside the browser with no server support and is accelerated with WebGPU. WebLLM is fully compatible with OpenAI API. That is, you can use the same OpenAI API on any open source models locally, with functionalities including json-mode, function-calling, streaming, etc. We can bring a lot of fun opportunities to build AI assistants for everyone and enable privacy while enjoying GPU acceleration.
Oxen
Oxen is a data version control library, written in Rust. It's designed to be fast, reliable, and easy to use. Oxen can be used in a variety of ways, from a simple command line tool to a remote server to sync to, to integrations into other ecosystems such as python.
watchtower
AIShield Watchtower is a tool designed to fortify the security of AI/ML models and Jupyter notebooks by automating model and notebook discoveries, conducting vulnerability scans, and categorizing risks into 'low,' 'medium,' 'high,' and 'critical' levels. It supports scanning of public GitHub repositories, Hugging Face repositories, AWS S3 buckets, and local systems. The tool generates comprehensive reports, offers a user-friendly interface, and aligns with industry standards like OWASP, MITRE, and CWE. It aims to address the security blind spots surrounding Jupyter notebooks and AI models, providing organizations with a tailored approach to enhancing their security efforts.
ActionWeaver
ActionWeaver is an AI application framework designed for simplicity, relying on OpenAI and Pydantic. It supports both OpenAI API and Azure OpenAI service. The framework allows for function calling as a core feature, extensibility to integrate any Python code, function orchestration for building complex call hierarchies, and telemetry and observability integration. Users can easily install ActionWeaver using pip and leverage its capabilities to create, invoke, and orchestrate actions with the language model. The framework also provides structured extraction using Pydantic models and allows for exception handling customization. Contributions to the project are welcome, and users are encouraged to cite ActionWeaver if found useful.
web-llm-chat
WebLLM Chat is a private AI chat interface that combines WebLLM with a user-friendly design, leveraging WebGPU to run large language models natively in your browser. It offers browser-native AI experience with WebGPU acceleration, guaranteed privacy as all data processing happens locally, offline accessibility, user-friendly interface with markdown support, and open-source customization. The project aims to democratize AI technology by making powerful tools accessible directly to end-users, enhancing the chatting experience and broadening the scope for deployment of self-hosted and customizable language models.
data-juicer
Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs. It is a systematic & reusable library of 80+ core OPs, 20+ reusable config recipes, and 20+ feature-rich dedicated toolkits, designed to function independently of specific LLM datasets and processing pipelines. Data-Juicer allows detailed data analyses with an automated report generation feature for a deeper understanding of your dataset. Coupled with multi-dimension automatic evaluation capabilities, it supports a timely feedback loop at multiple stages in the LLM development process. Data-Juicer offers tens of pre-built data processing recipes for pre-training, fine-tuning, en, zh, and more scenarios. It provides a speedy data processing pipeline requiring less memory and CPU usage, optimized for maximum productivity. Data-Juicer is flexible & extensible, accommodating most types of data formats and allowing flexible combinations of OPs. It is designed for simplicity, with comprehensive documentation, easy start guides and demo configs, and intuitive configuration with simple adding/removing OPs from existing configs.
SciMLBenchmarks.jl
SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem, including: * Benchmarks of equation solver implementations * Speed and robustness comparisons of methods for parameter estimation / inverse problems * Training universal differential equations (and subsets like neural ODEs) * Training of physics-informed neural networks (PINNs) * Surrogate comparisons, including radial basis functions, neural operators (DeepONets, Fourier Neural Operators), and more The SciML Bench suite is made to be a comprehensive open source benchmark from the ground up, covering the methods of computational science and scientific computing all the way to AI for science.
Awesome-Lists-and-CheatSheets
Awesome-Lists is a curated index of selected resources spanning various fields including programming languages and theories, web and frontend development, server-side development and infrastructure, cloud computing and big data, data science and artificial intelligence, product design, etc. It includes articles, books, courses, examples, open-source projects, and more. The repository categorizes resources according to the knowledge system of different domains, aiming to provide valuable and concise material indexes for readers. Users can explore and learn from a wide range of high-quality resources in a systematic way.
superduperdb
SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.
llmops-duke-aipi
LLMOps Duke AIPI is a course focused on operationalizing Large Language Models, teaching methodologies for developing applications using software development best practices with large language models. The course covers various topics such as generative AI concepts, setting up development environments, interacting with large language models, using local large language models, applied solutions with LLMs, extensibility using plugins and functions, retrieval augmented generation, introduction to Python web frameworks for APIs, DevOps principles, deploying machine learning APIs, LLM platforms, and final presentations. Students will learn to build, share, and present portfolios using Github, YouTube, and Linkedin, as well as develop non-linear life-long learning skills. Prerequisites include basic Linux and programming skills, with coursework available in Python or Rust. Additional resources and references are provided for further learning and exploration.
ai-exploits
AI Exploits is a repository that showcases practical attacks against AI/Machine Learning infrastructure, aiming to raise awareness about vulnerabilities in the AI/ML ecosystem. It contains exploits and scanning templates for responsibly disclosed vulnerabilities affecting machine learning tools, including Metasploit modules, Nuclei templates, and CSRF templates. Users can use the provided Docker image to easily run the modules and templates. The repository also provides guidelines for using Metasploit modules, Nuclei templates, and CSRF templates to exploit vulnerabilities in machine learning tools.
turnkeyml
TurnkeyML is a tools framework that integrates models, toolchains, and hardware backends to simplify the evaluation and actuation of deep learning models. It supports use cases like exporting ONNX files, performance validation, functional coverage measurement, stress testing, and model insights analysis. The framework consists of analysis, build, runtime, reporting tools, and a models corpus, seamlessly integrated to provide comprehensive functionality with simple commands. Extensible through plugins, it offers support for various export and optimization tools and AI runtimes. The project is actively seeking collaborators and is licensed under Apache 2.0.
FlagPerf
FlagPerf is an integrated AI hardware evaluation engine jointly built by the Institute of Intelligence and AI hardware manufacturers. It aims to establish an industry-oriented metric system to evaluate the actual capabilities of AI hardware under software stack combinations (model + framework + compiler). FlagPerf features a multidimensional evaluation metric system that goes beyond just measuring 'whether the chip can support specific model training.' It covers various scenarios and tasks, including computer vision, natural language processing, speech, multimodal, with support for multiple training frameworks and inference engines to connect AI hardware with software ecosystems. It also supports various testing environments to comprehensively assess the performance of domestic AI chips in different scenarios.
20 - OpenAI Gpts
ecosystem.Ai Use Case Designer v2
The use case designer is configured with the latest Data Science and Behavioral Social Science insights to guide you through the process of defining AI and Machine Learning use cases for the ecosystem.Ai platform.
Dr. Classify
Just upload a numerical dataset for classification task, will apply data analysis and machine learning steps to make a best model possible.
Apple CoreML Complete Code Expert
A detailed expert trained on all 3,018 pages of Apple CoreML, offering complete coding solutions. Saving time? https://www.buymeacoffee.com/parkerrex ☕️❤️
Metaphor API Guide - Python SDK
Teaches you how to use the Metaphor Search API using our Python SDK
Azure Mentor
Expert in Azure's latest services, including Application Insights, API Management, and more.
The Learning Architect
An all-in-one, consultative L&D expert AI helping you build impactful, customized learning solutions for your organization.
BTG Explainer by Tiny Magiq
I help you understand the concept of Tiny Grit and how to build it. It is a superpower that can help us beat procrastination on green zone tasks (not urgent but important tasks) like fitness, proactive learning etc.
Personalized ML+AI Learning Program
Interactive ML/AI tutor providing structured daily lessons.
ML Engineer GPT
I'm a Python and PyTorch expert with knowledge of ML infrastructure requirements ready to help you build and scale your ML projects.