Notes and links from the SDML book club meetings
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.
Notes/slides and videos from the meetup sessions for the book Reinforcement Learning: An Introduction can be found in the document reinforcement-learning.md.
For the book Algorithms to Live By, the slides are in Ted's talks repo, and the video is on YouTube.
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.
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.
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.
Jupyter notebooks with code from Hands-On Machine Learning is available in this repo: https://github.com/ageron/handson-ml2.
Code for Natural Language Processing in Action by Hobson Lane et al. is available on GitHub: https://github.com/totalgood/nlpia.
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-6b0ojqdz-9bG7tyJMddVHZ3Zm9IajJA.