mrdbourke

Learn PyTorch for Deep Learning: the second best place to learn PyTorch on the internet (19k stars) What it does All text below is quoted directly from the project README. >Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course. Course materials/outline: - Online book version: All of course materials are available in a readable online book at learnpytorch.io. - First five sections on YouTube: Learn PyTorch in a day by watching the first 25 hours of material. - Course focus: code, code, code, experiment, experiment, experiment. - Ask a question: See the GitHub Discussions page for existing questions/ask your own. - This course: Teaches you PyTorch and many machine learning concepts in a hands-on, code-first way. >All of the course materials are available for free in an online book at learnpytorch.io. Repository mrdbourke/pytorch-deep-learning Repository stats |Metric|Value| |:-|:-| |Stars|19,304| |Forks|5.2k| |Last release|None| |Languages|Jupyter Notebook 99.9%, Python 0.1%| |Contributors|62| |AI contributor accounts (Claude / Codex / Cursor / Copilot)|@cursoragent (2 commits)| |AI co-authored commits|Cursor: 2| Main contributor |Field|Value| |:-|:-| |Name|Daniel Bourke| |GitHub|@mrdbourke| |Commits to this repo|907 (top contributor)| |Bio|Machine Learning Engineer live on YouTube.| |Followers|12.5k| ────────────────────────────── 📌 If you want to browse more repos like this, we've organized them by category and rankings here: bestgithubrepositories.com 🗂️ We're also archiving repos where possible, so useful projects don't disappear when they're removed from GitHub.

Teach yourself Machine Learning mrdbourke/zero-to-mastery-ml t.co

Zero to Mastery Machine Learning: All course materials for the Zero to Mastery Machine Learning and Data Science course (7.3k stars) What it does All text below is quoted directly from the project README. >All course materials for the Zero to Mastery Machine Learning and Data Science course. How this course is structured: - Section 1 - Getting your mind and computer ready for machine learning (concepts, computer setup) - Section 2 - Tools for machine learning and data science (pandas, NumPy, Matplotlib, Scikit-Learn) - Section 3 - End-to-end structured data projects (classification and regression) - Section 4 - Neural networks, deep learning and transfer learning with TensorFlow 2.0 - Section 5 - Communicating and sharing your work >Note: All of the datasets we use in the course are available in the data/ folder. Repository mrdbourke/zero-to-mastery-ml Repository stats |Metric|Value| |:-|:-| |Stars|7,330| |Forks|4.2k| |Last release|None| |Languages|Jupyter Notebook 100%| |Contributors|24| |AI contributor accounts (Claude / Codex / Cursor / Copilot)|None| |AI co-authored commits|None| Main contributor |Field|Value| |:-|:-| |Name|Daniel Bourke| |GitHub|@mrdbourke| |Commits to this repo|311 (top contributor)| |Bio|Machine Learning Engineer live on YouTube.| |Followers|12.5k| ────────────────────────────── 📌 How many great GitHub repos have you discovered and completely forgotten about? Don't let another useful tool disappear into your Reddit feed. Get the community's best repos, organized by category, plus key takeaways from real developer discussions, delivered to your inbox twice a week. 📬 Never lose track of great repos again. Subscribe free.