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Notes, links and code samples and resources for teaching yourself pytorch and tensorflow.

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AI-101 🚀

Lecture notes, readings, code samples and resources for teaching yourself how PyTorch and Tensorflow.

This class was formerly taught as a bootcamp but is now a self-paced online resource.

More Like This ⭐

See Brad's GitHub Stars for a curated collection of helpful resources.

Course Outline 📝

Session Topic TODO
Preparation N/A See preparation.md
📅 Week 1 📚 Roles, Machine Learning Basics, Tech Stack How Deep Learning Works and Intro to Free Software
📅 Week 1 🎬 "Foundations" Live Demos SuperDataScience Code Interpreter Guide
📅 Week 2 💡 Final Project Ideas Pick a project!
📅 Week 2 📊 The Universal ML Workflow The Universal ML Workflow and The Regression Theory of Everything
📅 Week 3 👥 Pair Programming, Project Q&A work on your project
📅 Week 3 📝 Data Engineering, ETL Basics and Data Wrangling Techniques work on your project
📅 Week 4 📊 OpenRouter Sommelier App in AWS, Azure and GCP Cloud Setup Demo Setup AWS Free Tier
📅 Week 5 🧠 Metrics and Loss Functions, Model Architecture and Hyperparameters 60 Minute Pytorch Blitz
📅 Week 7 🎓 After The Bootcamp... go forth and win!
📅 Weeks 7-8 🎉 Project Presentations brag about yourself online

🚀 Final Project Sequence 🚀

Participants will dedicate substantial time to final projects aligned with their ✨career aspirations✨. For an array of past presentations and source code, 📺 visit Brad's Youtube Channel.

Step Details
🅰️ Data Collection and Simple Model Generate synthetic text data using Scikit-LLM. Explore datasets on Kaggle or Hugging Face.
🅱️ Custom Model (Optional) Beginner: Follow TensorFlow quickstart for basic image/text classifiers. Recommended: Dive into 60 Minute PyTorch Blitz, then explore 📜 PyTorch Text Classification or PyTorch Image Classification. More Advanced: Fine-tune pretrained models with Hugging Face for 📝 text or 📸 image classification. Apple Nerds Only Use MLX.
⭐ Challenge and Experiment (Optional) Advanced: Explore cross-platform frameworks like Keras Core. 🏆 Very Advanced: Attempt to Replicate a Winning Model from Kaggle.