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Andrew Ng’s Machine Learning at Stanford University

coursera.org

Andrew Ng’s Machine Learning at Stanford University is a Coursera course titled 'Supervised Machine Learning: Regression and Classification'. It is the first course of the Machine Learning Specialization. The course teaches how to build machine learning models in Python using NumPy and scikit-learn, covering regression and classification. It is aimed at beginners, requires flexible scheduling over three weeks at ten hours per week, and offers a shareable certificate.

Deep Learning Drizzle is a collection of links to university and instructor lecture materials on deep learning and related machine learning topics. It lists courses by title, instructor or institution, course webpage, lecture videos and year. Topics include neural networks, natural language processing, computer vision, reinforcement learning, Bayesian deep learning, medical imaging and graph neural networks.

Machine Learning Roadmap

rentry.org

A staged learning roadmap for machine learning that covers mathematics and calculus, programming, and machine learning concepts. It advises moving to the next stage only after fully understanding the current one. The mathematics section covers linear algebra, calculus, and probability and statistics, and the programming section covers Python basics and advanced Python.

Data School

dataschool.io

Data School is a blog about data science and machine learning. Its posts cover topics such as the difference between AI and machine learning, learning scikit-learn, AI progress, and using pandas for calculations. Posts are tagged by subject including Python, AI, and machine learning.

H2O

github.com

H2O is an open-source, distributed, fast, and scalable machine learning platform hosted on GitHub by the h2oai organization. It supports a wide range of machine learning methods including deep learning, gradient boosting, random forest, generalized linear modeling, clustering, dimensionality reduction, rule fitting, support vector machines, stacked ensembles, and automated machine learning.

cl-online-learning

github.com

cl-online-learning is a Common Lisp library collecting machine learning algorithms for online linear classification. It implements binary classifiers including Perceptron, AROW, SCW-I, logistic regression with SGD or ADAM, and FTRL-Proximal, plus multiclass approaches such as one-vs-rest, one-vs-one, multiclass AROW and softmax with FTRL-Proximal. Command line tools are provided as a roswell script, and the package is available from Quicklisp.

Niraj-Lunavat/Artificial-Intelligence

github.com

A GitHub repository collecting AI learning resources, including over 100 cheat-sheets, free online books, courses, videos and lectures, papers, tutorials, researchers, websites, datasets, conferences, frameworks and tools. Topics include machine learning, deep learning, big data, data science and Python.

Full Stack Deep Learning

fullstackdeeplearning.com

Full Stack Deep Learning offers news, community, and courses for people building AI-powered products. It covers the lifecycle of an AI-powered product, from defining the problem and picking a GPU or foundation model to production deployment and continual learning.

Sebastian Thrun’s Introduction To Machine Learning

udacity.com

Sebastian Thrun’s Introduction To Machine Learning provides AI-assisted learning, courses, tutorials, or study support.

Approaching (Almost) Any Machine Learning Problem

github.com

Approaching (Almost) Any Machine Learning Problem is a GitHub repository or organization with source code, releases, documentation, or project.

GeoGebra

geogebra.org

GeoGebra is an interactive mathematics platform for teaching and learning. It provides free digital tools including calculators, graphing, geometry, 3D exploration, and collaborative whiteboard features. The platform offers ready-made educational resources for grades 4 to 12, tools for users to create custom materials, and classroom functionality for teachers to track student progress and provide feedback. It integrates with various learning management systems and is used by teachers and students at school and university levels.

Supports teaching, studying or skills practice with AI-guided learning tools.

Machine Learning Visualized

github.com

Machine Learning Visualized is a GitHub repository or organization with source code, releases, documentation, or project resources.

Alison

alison.com

Alison is a free online learning platform that provides free online courses with certificates and diplomas. It has over 6,000 courses across categories including information technology, health, language, business, management, and personal development. The platform has more than 50 million learners and over 15 million graduates from 193 countries. It offers a mobile app for offline learning, business training for organizations, and free tools including English courses, psychometric tests, career guidance, and a resume builder.

Awesome AutoML Papers

github.com

Awesome AutoML Papers is a GitHub-hosted curated list focused on automated machine learning (AutoML). It aggregates academic papers, articles, tutorials, slide decks, and related projects in the AutoML field, serving as a centralized reference for users exploring automated machine learning research and developments.

Awesome Federated Learning Systems

github.com

A curated GitHub list of federated learning system papers, articles, tutorials, slides and projects. It groups entries such as systems from big tech companies, vertical FL, open-source frameworks, edge and mobile systems, optimization, security and privacy, applications and surveys. Papers reviewed and presented at academic conferences are marked with a graduation cap symbol.

Coach

github.com

Reinforcement Learning Coach by Intel® AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms.

Cognitive Class AI by IBM

cognitiveclass.ai

Cognitive Class AI by IBM is a free online learning platform. It offers over 100 courses, 300 hands-on projects and 20 learning paths covering AI, cloud computing, full-stack development, cybersecurity, data science and other technology fields. Learners can earn certificates and badges, and the platform serves over 3 million learners.

coursera-deep-learning-specialization

github.com

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai.

Data Science 101

ryanswanstrom.com

Data Science 101 is a blog started in 2012 by Ryan Swanstrom about learning to become a data scientist. It covers getting started, data science career tips, free learning resources, videos, and academic papers.

Donkuri

donkuri.github.io

Immersion-Based Japanese Learning is a website explaining an input-driven, immersion-based language learning method with a focus on Japanese. It sets out to argue for the method, provide a learning setup, and list learning resources and Japanese media recommendations.

Gym4ReaL

github.com

Gym4ReaL is an open-source GitHub repository maintained by Daveonwave. It is a Gymnasium-based benchmarking suite for testing reinforcement learning algorithms on real-world scenarios. The repository includes documentation on supported characteristics, reinforcement learning paradigms, folder structure, contribution guidelines, and licensing terms.

Jingles

jinglescode.github.io

Hong Jing (Jingles) is a data scientist and Alibaba PhD student who writes about machine learning and neuroscience. The site collects blog articles on topics such as reinforcement learning agents, learned optimizers, convolutional layers, transformer models and decoding brain signals.

An introductory machine learning course taught by Caltech Professor Yaser Abu-Mostafa, recorded from a live broadcast and available as a free online MOOC. It covers basic theory, algorithms and applications across 18 lectures, with homework sets and a final exam. Prerequisites are basic probability, matrices and calculus.