Code examples for the O'Reilly book Hands-On Large Language Models, covering LLM concepts and practical techniques in Jupyter notebooks.
A free, self-paced computer science curriculum assembled from online courses and books, modeled on undergraduate CS degree requirements.
Jupyter notebooks and recipes demonstrating code patterns for building with the Claude API, including tool use, RAG, vision, and evaluations.
Course materials, code, notebooks and datasets for the Zero to Mastery Machine Learning and Data Science course.
Example notebooks and guides showing how to accomplish common tasks with the OpenAI API.
A collection of 42+ runnable Jupyter notebooks, each tutorial covering an advanced technique for Retrieval-Augmented Generation systems.
A Chinese-language book by Li Xiaolai teaching self-learning skills through a Python programming curriculum, delivered as Jupyter notebooks.
Source repository for Simon Prince's textbook Understanding Deep Learning, with LaTeX sources, figures, and Jupyter notebooks.
Jupyter notebooks and code accompanying Ed Donner's 8-week LLM engineering course, from local models through building LLM applications.
Developer hub with training recipes, cookbooks, datasets, and end-to-end examples for building with NVIDIA's open Nemotron models.
Sample notebooks, code, and apps demonstrating how to build with generative AI models on Google Cloud.
Jupyter notebooks and code samples accompanying Wes McKinney's book on data analysis with Python, pandas, and NumPy.
A video course with Jupyter notebooks that builds neural networks and backpropagation from scratch, from basics to Transformer language models.
A collection of Jupyter notebook exercises with instructions and solutions for practicing pandas skills by topic.