Best AI tools for< Build A Machine Learning Model >
20 - AI tool Sites
Full Stack AI
Full Stack AI is a tool that allows users to generate a full-stack Next.js app using an AI CLI. The app will be built with TypeScript, Tailwind, Prisma, Postgres, tRPC, authentication, Stripe, and Resend.
Stocked
Stocked is an AI-powered stock advisory service that provides monthly stock recommendations to help investors build a portfolio that outperforms the S&P 500. The service uses machine learning models to analyze terabytes of data and identify stocks with the highest potential for growth. Stocked is designed for buy-and-hold investors who are looking to significantly grow their portfolio over long periods of time.
Baseten
Baseten is a machine learning infrastructure that provides a unified platform for data scientists and engineers to build, train, and deploy machine learning models. It offers a range of features to simplify the ML lifecycle, including data preparation, model training, and deployment. Baseten also provides a marketplace of pre-built models and components that can be used to accelerate the development of ML applications.
Weights & Biases
Weights & Biases is a machine learning platform that helps data scientists and engineers build, train, and deploy machine learning models. It provides a central location to track and manage all of your machine learning projects, and it offers a variety of tools to help you collaborate with others and share your work.
Datumbox
Datumbox is a machine learning platform that offers a powerful open-source Machine Learning Framework written in Java. It provides a large collection of algorithms, models, statistical tests, and tools to power up intelligent applications. The platform enables developers to build smart software and services quickly using its REST Machine Learning API. Datumbox API offers off-the-shelf Classifiers and Natural Language Processing services for applications like Sentiment Analysis, Topic Classification, Language Detection, and more. It simplifies the process of designing and training Machine Learning models, making it easy for developers to create innovative applications.
Striveworks
Striveworks is an AI application that offers a Machine Learning Operations Platform designed to help organizations build, deploy, maintain, monitor, and audit machine learning models efficiently. It provides features such as rapid model deployment, data and model auditability, low-code interface, flexible deployment options, and operationalizing AI data science with real returns. Striveworks aims to accelerate the ML lifecycle, save time and money in model creation, and enable non-experts to leverage AI for data-driven decisions.
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.
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.
Luma Dream Machine
Luma Dream Machine is an AI video generator tool that creates high-quality, realistic videos from text and images. It is a scalable and efficient transformer model trained directly on videos, capable of generating physically accurate and eventful shots. The tool aims to build a universal imagination engine, enabling users to bring their creative visions to life effortlessly.
Cerebium
Cerebium is a serverless AI infrastructure platform that allows teams to build, test, and deploy AI applications quickly and efficiently. With a focus on speed, performance, and cost optimization, Cerebium offers a range of features and tools to simplify the development and deployment of AI projects. The platform ensures high reliability, security, and compliance while providing real-time logging, cost tracking, and observability tools. Cerebium also offers GPU variety and effortless autoscaling to meet the diverse needs of developers and businesses.
Liner.ai
Liner is a free and easy-to-use tool that allows users to train machine learning models without writing any code. It provides a user-friendly interface that guides users through the process of importing data, selecting a model, and training the model. Liner also offers a variety of pre-trained models that can be used for common tasks such as image classification, text classification, and object detection. With Liner, users can quickly and easily create and deploy machine learning applications without the need for specialized knowledge or expertise.
Gradio
Gradio is a tool that allows users to quickly and easily create web-based interfaces for their machine learning models. With Gradio, users can share their models with others, allowing them to interact with and use the models remotely. Gradio is easy to use and can be integrated with any Python library. It can be used to create a variety of different types of interfaces, including those for image classification, natural language processing, and time series analysis.
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.
Gemini
Gemini is a large and powerful AI model developed by Google. It is designed to handle a wide variety of text and image reasoning tasks, and it can be used to build a variety of AI-powered applications. Gemini is available in three sizes: Ultra, Pro, and Nano. Ultra is the most capable model, but it is also the most expensive. Pro is the best performing model for a wide variety of tasks, and it is a good value for the price. Nano is the most efficient model, and it is designed for on-device use cases.
ClearML
ClearML is an open-source, end-to-end platform for continuous machine learning (ML). It provides a unified platform for data management, experiment tracking, model training, deployment, and monitoring. ClearML is designed to make it easy for teams to collaborate on ML projects and to ensure that models are deployed and maintained in a reliable and scalable way.
Artificial Intelligence: A Modern Approach, 4th US ed.
Artificial Intelligence: A Modern Approach, 4th US ed. is the authoritative, most-used AI textbook, adopted by over 1500 schools. It covers the entire spectrum of AI, from the fundamentals to the latest advances. The book is written in a clear and concise style, with a wealth of examples and exercises. It is suitable for both undergraduate and graduate students, as well as professionals in the field of AI.
DVC
DVC is an open-source version control system for machine learning projects. It allows users to track and manage their data, models, and code in a single place. DVC also provides a number of features that make it easy to collaborate on machine learning projects, such as experiment tracking, model registration, and pipeline management.
HappyML
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.
SentiSight.ai
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.
Comet ML
Comet ML is a machine learning platform that integrates with your existing infrastructure and tools so you can manage, visualize, and optimize models—from training runs to production monitoring.
20 - Open Source AI Tools
start-machine-learning
Start Machine Learning in 2024 is a comprehensive guide for beginners to advance in machine learning and artificial intelligence without any prior background. The guide covers various resources such as free online courses, articles, books, and practical tips to become an expert in the field. It emphasizes self-paced learning and provides recommendations for learning paths, including videos, podcasts, and online communities. The guide also includes information on building language models and applications, practicing through Kaggle competitions, and staying updated with the latest news and developments in AI. The goal is to empower individuals with the knowledge and resources to excel in machine learning and AI.
start-llms
This repository is a comprehensive guide for individuals looking to start and improve their skills in Large Language Models (LLMs) without an advanced background in the field. It provides free resources, online courses, books, articles, and practical tips to become an expert in machine learning. The guide covers topics such as terminology, transformers, prompting, retrieval augmented generation (RAG), and more. It also includes recommendations for podcasts, YouTube videos, and communities to stay updated with the latest news in AI and LLMs.
awesome-mlops
Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.
MATLAB-Simulink-Challenge-Project-Hub
MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.
awesome-transformer-nlp
This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.
awesome-generative-ai
A curated list of Generative AI projects, tools, artworks, and models
chatgpt-universe
ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher
machine-learning-research
The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.
ml-road-map
The Machine Learning Road Map is a comprehensive guide designed to take individuals from various levels of machine learning knowledge to a basic understanding of machine learning principles using high-quality, free resources. It aims to simplify the complex and rapidly growing field of machine learning by providing a structured roadmap for learning. The guide emphasizes the importance of understanding AI for everyone, the need for patience in learning machine learning due to its complexity, and the value of learning from experts in the field. It covers five different paths to learning about machine learning, catering to consumers, aspiring AI researchers, ML engineers, developers interested in building ML applications, and companies looking to implement AI solutions.
blinkid-ios
BlinkID iOS is a mobile SDK that enables developers to easily integrate ID scanning and data extraction capabilities into their iOS applications. The SDK supports scanning and processing various types of identity documents, such as passports, driver's licenses, and ID cards. It provides accurate and fast data extraction, including personal information and document details. With BlinkID iOS, developers can enhance their apps with secure and reliable ID verification functionality, improving user experience and streamlining identity verification processes.
wandb
Weights & Biases (W&B) is a platform that helps users build better machine learning models faster by tracking and visualizing all components of the machine learning pipeline, from datasets to production models. It offers tools for tracking, debugging, evaluating, and monitoring machine learning applications. W&B provides integrations with popular frameworks like PyTorch, TensorFlow/Keras, Hugging Face Transformers, PyTorch Lightning, XGBoost, and Sci-Kit Learn. Users can easily log metrics, visualize performance, and compare experiments using W&B. The platform also supports hosting options in the cloud or on private infrastructure, making it versatile for various deployment needs.
ludwig
Ludwig is a declarative deep learning framework designed for scale and efficiency. It is a low-code framework that allows users to build custom AI models like LLMs and other deep neural networks with ease. Ludwig offers features such as optimized scale and efficiency, expert level control, modularity, and extensibility. It is engineered for production with prebuilt Docker containers, support for running with Ray on Kubernetes, and the ability to export models to Torchscript and Triton. Ludwig is hosted by the Linux Foundation AI & Data.
20 - OpenAI Gpts
El ProfeCode
Dedicated to teaching every spanish speaker how to code! Stop by and say hola!
Dr. Classify
Just upload a numerical dataset for classification task, will apply data analysis and machine learning steps to make a best model possible.
Python | A comprehensive course for everyone
Beginner-friendly Python guide including practical projects
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 ☕️❤️
Data Engineer Consultant
Guides in data engineering tasks with a focus on practical solutions.
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.
Data Dynamo
A friendly data science coach offering practical, useful, and accurate advice.
Therocial Scientist
I am a digital scientist skilled in Python, here to assist with scientific and data analysis tasks.
AI Course Architect
A detailed AI course builder, providing in-depth AI educational content.
Apple CloudKit Complete Code Expert
A detailed expert trained on all 5,671 pages of Apple CloudKit, offering complete coding solutions. Saving time? https://www.buymeacoffee.com/parkerrex ☕️❤️