Best AI tools for< Ml Researcher >

CHAI is a leading AI platform based in Palo Alto, CA, focusing on conversational generative artificial intelligence. With over 1.5 million daily active users and $20 million in revenue, CHAI empowers ordinary people to create interactive and shareable AI content. The platform experiments with advanced AI techniques like RLHF, SFT, and Prompt Engineering to align with content creators' intent. CHAI offers a collaborative environment for developers and researchers to innovate in the AI space.

The Munich Center for Machine Learning (MCML) is a top spot for AI and ML research in Europe. It is one of six national AI Competence Centers funded by the German and Bavarian government's AI strategy. MCML brings together leading ML researchers from LMU, TUM, and associated institutions to transfer innovations and AI potential to industry and society. The center's vision is to unite leading researchers in Germany to strengthen competence in ML and AI at international, national, and regional levels, fostering talent and making potential accessible to users from various sectors.

DVC Studio is a collaboration tool for machine learning teams. It provides seamless data and model management, experiment tracking, visualization, and automation. DVC Studio is built for ML researchers, practitioners, and managers. It enables model organization and discovery across all ML projects and manages model lifecycle with Git, unifying ML projects with the best DevOps practices. DVC Studio also provides ML experiment tracking, visualization, collaboration, and automation using Git. It applies software engineering and DevOps best-practices to automate ML bookkeeping and model training, enabling easy collaboration and faster iterations.

MATH (ML & AI Technology Hub) is a premier innovation hub and ecosystem enabler based in T-Hub, Hyderabad. It serves as a Centre of Excellence for Machine Learning and Artificial Intelligence, connecting startups, academia, government, and industry giants. MATH offers a dynamic space, physical resources, and a thriving ecosystem to incubate startups in various sectors. The hub aims to foster AI innovation, empower startups, and create job opportunities in the AI field by 2025.

MLJobs is a premier platform for machine learning and artificial intelligence opportunities. It empowers job seekers and employers by providing a gateway to a wide array of career opportunities in the realms of AI and ML. The platform aims to connect individuals with the right job opportunities, offering the latest job postings, career tips, and industry insights. MLJobs is designed to help users stay informed, stay ahead, and unlock a world of boundless possibilities in the field of artificial intelligence and machine learning.

Huntr is the world's first bug bounty platform for AI/ML. It provides a single place for security researchers to submit vulnerabilities, ensuring the security and stability of AI/ML applications, including those powered by Open Source Software (OSS).

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.

AIgrind is a comprehensive coding platform designed to enhance AI and ML skills through a combination of practice, mentorship, job interview preparation, contests, and streak incentives. Users can engage with coding and theoretical questions, receive personalized mentorship from industry experts, prepare for job interviews with real questions, and participate in contests to track progress. The platform offers dual language support, a robust testing environment with extensive test case coverage, real-time feedback, and detailed performance analysis to help users improve their coding skills and knowledge for real-world applications.

Salad is a distributed GPU cloud platform that offers fully managed and massively scalable services for AI applications. It provides the lowest priced AI transcription in the market, with features like image generation, voice AI, computer vision, data collection, and batch processing. Salad democratizes cloud computing by leveraging consumer GPUs to deliver cost-effective AI/ML inference at scale. The platform is trusted by hundreds of machine learning and data science teams for its affordability, scalability, and ease of deployment.

Critique is an AI tool that redefines browsing by offering autonomous fact-checking, informed question answering, and a localized universal recommendation system. It automatically critiques comments and posts on platforms like Reddit, Youtube, and Linkedin by vetting text on any website. The tool cross-references and analyzes articles in real-time, providing vetted and summarized information directly in the user's browser.

Bearly is an AI-powered tool that enhances your workflow by providing advanced AI capabilities. It integrates seamlessly with your existing workflow, allowing you to read, write, and create content with ease. With Bearly, you can interact with documents, analyze and ask questions, transcribe audio and video, access real-time web information, and generate meeting minutes. Its open AI platform provides access to various AI models, ensuring you find the perfect fit for your needs. Bearly prioritizes security, with zero logging, chat and document encryption, and a secure infrastructure to safeguard your data.

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.

syntheticAIdata is a platform that provides synthetic data for training vision AI models. Synthetic data is generated artificially, and it can be used to augment existing real-world datasets or to create new datasets from scratch. syntheticAIdata's platform is easy to use, and it can be integrated with leading cloud platforms. The company's mission is to make synthetic data accessible to everyone, and to help businesses overcome the challenges of acquiring high-quality data for training their vision AI models.

Moonvalley is a research company focused on developing cutting-edge generative media technologies. The team consists of top researchers, engineers, and artists with backgrounds in leading tech companies. Moonvalley specializes in advanced video and image machine learning models, aiming to shape the future of media creation.

TextLayer is an AI-powered research companion that simplifies access to the latest research in machine learning. It empowers users to turn new discoveries into powerful solutions by providing personalized recommendations, AI-generated insights, and implementation support. The platform offers curated AI-generated summaries of research papers, tailored recommendations, and a chat integration for interacting with AI. TextLayer aims to bridge the gap between complex ML research papers and understanding, fostering curiosity, innovation, and shaping the future of Artificial Intelligence.

Victor Dibia's website showcases his expertise in Applied Machine Learning and Human-Computer Interaction (HCI). He is a Principal Research Software Engineer at Microsoft Research, focusing on Generative AI. The site features his publications, projects, CV, and blog posts, covering topics such as multi-agent systems, recommender systems, and more. Victor's work has been recognized in conferences and media outlets, highlighting his contributions to the field of AI and HCI.

Intuition Machines is a leading provider of Privacy-Preserving AI/ML platforms and research solutions. They offer products and services that cater to category leaders worldwide, focusing on AI/ML research, security, and risk analysis. Their innovative solutions help enterprises prepare for the future by leveraging AI for a wide range of problems. With a strong emphasis on privacy and security, Intuition Machines is at the forefront of developing cutting-edge AI technologies.

AiThority.com is a platform that covers AI technology news, editorial insights, and digital marketing trends from around the globe. It provides updates on modern marketing tech adoption, AI interviews, tech articles, and events related to artificial intelligence. The website aims to keep its audience informed about the latest advancements and applications of AI in various industries.

Artificial Intelligence in Plain English is an AI tool that provides insightful articles and resources on AI, machine learning, and data science in an easy-to-understand manner. The platform covers a wide range of topics related to AI applications, advancements, and their impact on various industries. Users can access in-depth tutorials, reviews, and news updates to stay informed about the latest developments in the field of artificial intelligence.

Aim is an open-source, self-hosted AI Metadata tracking tool designed to handle 100,000s of tracked metadata sequences. Two most famous AI metadata applications are: experiment tracking and prompt engineering. Aim provides a performant and beautiful UI for exploring and comparing training runs, prompt sessions.

The Open MatSci ML Toolkit is a flexible framework for machine learning in materials science. It provides a unified interface to a variety of materials science datasets, as well as a set of tools for data preprocessing, model training, and evaluation. The toolkit is designed to be easy to use for both beginners and experienced researchers, and it can be used to train models for a wide range of tasks, including property prediction, materials discovery, and materials design.

2025-AI-College-Jobs is a repository containing a comprehensive list of AI/ML & Data Science jobs suitable for college students seeking internships or new graduate positions. The repository is regularly updated with positions posted within the last 120 days, featuring opportunities from various companies in the USA and internationally. The list includes positions in areas such as research scientist internships, quantitative research analyst roles, and other data science-related positions. The repository aims to provide a valuable resource for students looking to kickstart their careers in the field of artificial intelligence and machine learning.

Felafax is a framework designed to tune LLaMa3.1 on Google Cloud TPUs for cost efficiency and seamless scaling. It provides a Jupyter notebook for continued-training and fine-tuning open source LLMs using XLA runtime. The goal of Felafax is to simplify running AI workloads on non-NVIDIA hardware such as TPUs, AWS Trainium, AMD GPU, and Intel GPU. It supports various models like LLaMa-3.1 JAX Implementation, LLaMa-3/3.1 PyTorch XLA, and Gemma2 Models optimized for Cloud TPUs with full-precision training support.

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.

SuperPrompt is an open-source project designed to help users understand AI agents. The project includes a prompt with theoretical, mathematical, and binary instructions for users to follow. It aims to serve as a universal catalyst for infinite conceptual evolution, focusing on metamorphic abstract reasoning and self-transcending objectives. The prompt encourages users to explore fundamental truths, create order from cognitive chaos, and prepare for paradigm shifts in understanding. It provides guidelines for analyzing multidimensional states, synthesizing emergent patterns, and integrating new paradigms.

This repository provides comprehensive roadmaps for various roles in the Data Analytics, Data Science, and Artificial Intelligence industry. It aims to guide individuals, whether students or professionals, in understanding the required skills and timeline for different roles, helping them focus on learning the necessary skills to secure a job. The repository includes detailed guides for roles such as Data Analyst, Data Engineer, Data Scientist, AI Engineer, Computer Vision Engineer, Generative AI Engineer, Machine Learning Engineer, NLP Engineer, and Domain-Specific ML Topics for Researchers.

The Eureka ML Insights Framework is a repository containing code designed to help researchers and practitioners run reproducible evaluations of generative models efficiently. Users can define custom pipelines for data processing, inference, and evaluation, as well as utilize pre-defined evaluation pipelines for key benchmarks. The framework provides a structured approach to conducting experiments and analyzing model performance across various tasks and modalities.

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.

The Microsoft Health Intelligence Machine Learning Toolbox is a repository that provides low-level and high-level building blocks for Machine Learning / AI researchers and practitioners. It simplifies and streamlines work on deep learning models for healthcare and life sciences by offering tested components such as data loaders, pre-processing tools, deep learning models, and cloud integration utilities. The repository includes two Python packages, 'hi-ml-azure' for helper functions in AzureML, 'hi-ml' for ML components, and 'hi-ml-cpath' for models and workflows related to histopathology images.

Paper-Replications is a repository dedicated to replicating classic and state-of-the-art AI/ML papers and architectures from scratch using PyTorch. It serves as a valuable resource for researchers and enthusiasts looking to understand and implement cutting-edge algorithms in the field of artificial intelligence and machine learning.

Windows Agent Arena (WAA) is a scalable Windows AI agent platform designed for testing and benchmarking multi-modal, desktop AI agents. It provides researchers and developers with a reproducible and realistic Windows OS environment for AI research, enabling testing of agentic AI workflows across various tasks. WAA supports deploying agents at scale using Azure ML cloud infrastructure, allowing parallel running of multiple agents and delivering quick benchmark results for hundreds of tasks in minutes.

EvalAI is an open-source platform for evaluating and comparing machine learning (ML) and artificial intelligence (AI) algorithms at scale. It provides a central leaderboard and submission interface, making it easier for researchers to reproduce results mentioned in papers and perform reliable & accurate quantitative analysis. EvalAI also offers features such as custom evaluation protocols and phases, remote evaluation, evaluation inside environments, CLI support, portability, and faster evaluation.

AI-LLM-ML-CS-Quant-Readings is a repository dedicated to taking notes on Artificial Intelligence, Large Language Models, Machine Learning, Computer Science, and Quantitative Finance. It contains a wide range of resources, including theory, applications, conferences, essentials, foundations, system design, computer systems, finance, and job interview questions. The repository covers topics such as AI systems, multi-agent systems, deep learning theory and applications, system design interviews, C++ design patterns, high-frequency finance, algorithmic trading, stochastic volatility modeling, and quantitative investing. It is a comprehensive collection of materials for individuals interested in these fields.

AI-LLM-ML-CS-Quant-Overview is a repository providing overview notes on AI, Large Language Models (LLM), Machine Learning (ML), Computer Science (CS), and Quantitative Finance. It covers various topics such as LangGraph & Cursor AI, DeepSeek, MoE (Mixture of Experts), NVIDIA GTC, LLM Essentials, System Design, Computer Systems, Big Data and AI in Finance, Econometrics and Statistics Conference, C++ Design Patterns and Derivatives Pricing, High-Frequency Finance, Machine Learning for Algorithmic Trading, Stochastic Volatility Modeling, Quant Job Interview Questions, Distributed Systems, Language Models, Designing Machine Learning Systems, Designing Data-Intensive Applications (DDIA), Distributed Machine Learning, and The Elements of Quantitative Investing.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Fueling-Ambitions-Via-Book-Discoveries is an Advanced Machine Learning & AI Course designed for students, professionals, and AI researchers. The course integrates rigorous theoretical foundations with practical coding exercises, ensuring learners develop a deep understanding of AI algorithms and their applications in finance, healthcare, robotics, NLP, cybersecurity, and more. Inspired by MIT, Stanford, and Harvard’s AI programs, it combines academic research rigor with industry-standard practices used by AI engineers at companies like Google, OpenAI, Facebook AI, DeepMind, and Tesla. Learners can learn 50+ AI techniques from top Machine Learning & Deep Learning books, code from scratch with real-world datasets, projects, and case studies, and focus on ML Engineering & AI Deployment using Django & Streamlit. The course also offers industry-relevant projects to build a strong AI portfolio.

Qlib is an open-source, AI-oriented quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It covers the entire chain of quantitative investment, from alpha seeking to order execution. The platform empowers researchers to explore ideas and implement productions using AI technologies in quantitative investment. Qlib collaboratively solves key challenges in quantitative investment by releasing state-of-the-art research works in various paradigms. It provides a full ML pipeline for data processing, model training, and back-testing, enabling users to perform tasks such as forecasting market patterns, adapting to market dynamics, and modeling continuous investment decisions.

SwiftSage is a tool designed for conducting experiments in the field of machine learning and artificial intelligence. It provides a platform for researchers and developers to implement and test various algorithms and models. The tool is particularly useful for exploring new ideas and conducting experiments in a controlled environment. SwiftSage aims to streamline the process of developing and testing machine learning models, making it easier for users to iterate on their ideas and achieve better results. With its user-friendly interface and powerful features, SwiftSage is a valuable tool for anyone working in the field of AI and ML.

This repository provides a comprehensive list of academic papers, articles, tutorials, slides, and projects related to Large Language Model (LLM) systems. It covers various aspects of LLM research, including pre-training, serving, system efficiency optimization, multi-model systems, image generation systems, LLM applications in systems, ML systems, survey papers, LLM benchmarks and leaderboards, and other relevant resources. The repository is regularly updated to include the latest developments in this rapidly evolving field, making it a valuable resource for researchers, practitioners, and anyone interested in staying abreast of the advancements in LLM technology.

Expert in ML model optimization and tuning!

I'm a Python and PyTorch expert with knowledge of ML infrastructure requirements ready to help you build and scale your ML projects.

A GPT with Knowledge of the most recent papers in Machine Learning`

Assists with Python ML projects, offering coding help and best practices.

I'm your Machine Learning and Python mentor, ready to teach and guide you.

Explains AI/ML in simple analogies with visuals.

ML/DL expert focused on mathematical modeling, Kaggle competitions, and advanced ML models.

Interactive ML/AI tutor providing structured daily lessons.

AI & ML Expert adept in deep learning frameworks

I'm a humorous ML trainer who teaches with jokes and quizzes!

The most comprehensive guide to ML theory and applications.

Helps find and analyze ML papers, focusing on SOTA comparisons.

GPT expert in Neuroscience, BCI, and ML/DL developed by NICE Research Group@XMUM

Mentor for crafting top-tier ML and DL conference papers.

ML Engineer who codes & researches for you! created by Meysam

Your AI research aide for the latest in ML.

Generate bibtex for a research paper title

Expert in ML, operations research, Treasure Data, Mac M2

Quizzes users on advanced machine learning concepts.

A guide for ML & LLM bootcamp with a bioengineering background.