Notes and links from the SDML book club meetings. For slides and videos from other, non-book machine learning talks, please see the SDML talks repo.

Understanding Deep Learning

The schedule, notes/slides, recordings, and additional materials for the meetup sessions for Understanding Deep Learning can be found in the document understanding-deep-learning.md.

Generative AI with Large Language Models (LLMs)

SDML is going through this new course by DeepLearning.AI on Coursera

• Kickoff meeting slides and video
• Week 1 discussion slides and video
• Week 2 discussion slides and video
• Week 3 slides and video

Probabilistic Machine Learning: Advanced Topics

Materials for the book reading group for the book Probabilistic Machine Learning: Advanced Topics, which started in January 2023, can be found in the document probabilistic-ml.md.

Learning SQL Queries

Notes/slides, videos, schedule, and additional materials for the meetup sessions for the Learning SQL series, using the book Sams Teach Yourself SQL in 10 Minutes, which started in September 2022, can be found in the document sql-queries.md.

Quantum Computing

Videos, schedule, and additional materials for the meetup sessions for the Quantum Computing series, using the book Dancing with Qubits, which started in August 2022, can be found in the document quantum-computing.md.

Machine Learning with Graphs

Notes/slides and videos from the meetup sessions for Machine Learning with Graphs, which started in January 2022, can be found in the document machine-learning-with-graphs.md.

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition

Notes/slides and videos from the meetup sessions for the book Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, which started in October 2021, can be found in the document hands-on-machine-learning.md.

Reinforcement Learning

Notes/slides and videos from the meetup sessions for the book Reinforcement Learning: An Introduction can be found in the document reinforcement-learning.md.

Algorithms to Live By

For the book Algorithms to Live By, the slides are in Ted's talks repo, and the video is on YouTube.

Designing Data-Intensive Applications

Notes and videos from the meetup sessions for the book Designing Data-Intensive Applications can be found in the document designing-data-intensive-apps.md.

Deep Learning with PyTorch

Notes and videos from the meetup sessions for the book Deep Learning with PyTorch can be found in the document deep-learning-with-pytorch.md.

Feature Engineering for Machine Learning

The book Feature Engineering for Machine Learning by Alice Zheng & Amanda Casari comes with a set of Jupyter notebooks so that you can run the code examples in the book. The notebooks for the book are located in the GitHub repository https://github.com/alicezheng/feature-engineering-book.

The notebook with instructions and code for downloading the datasets not contained in the book repo is located in this repo https://github.com/tedkyi/feature-engineering.

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition -- 2019

Jupyter notebooks with code from Hands-On Machine Learning is available in this repo: https://github.com/ageron/handson-ml2.

Natural Language Processing in Action

Code for Natural Language Processing in Action by Hobson Lane et al. is available on GitHub: https://github.com/totalgood/nlpia.

Additional information

For slides and videos from machine learning talks, please see the SDML talks repo.

To stay in touch with San Diego Machine Learning and receive announcements of all of our events, join our Meetup group https://www.meetup.com/San-Diego-Machine-Learning.

For more events, job postings, and discussion of machine learning, join our slack channel https://join.slack.com/t/sdmachinelearning/shared_invite/zt-2b2207qhg-Iyys1g0Ot6iErTYMioV9Mg