Representation Learning and Generative Learning Using Autoencoders and GANs

Representation Learning and Generative Learning Using Autoencoders and GANs Discussion leader: Robert Kraig This week we will discuss encoding images into and generating images from lower dimensional spaces. This material is in chapter 17 of the book Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (2nd Edition) by Aurélien Géron. The SDML book club will be meeting Saturdays to discuss one chapter each week. The HOML book is available from different booksellers. Make sure to get the second edition with the color cover, not the first edition with the red cover. This is simply one of the best data science books out there. The book covers all of the core concepts from basics like what is machine learning and linear regression to advanced models like reinforcement learning and GANs. This material will provide a solid foundation for beginners, and further the understanding for more experienced data scientists. https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/ Agenda 12:00 - 12:15 pm -- Arrival 12:15 - 1:30 pm -- Representation Learning and Generative Learning Using Autoencoders and GANs Time permitting -- Additional breakouts Links to chapter notes and videos of prior meetups are available on the SDML GitHub repo https://github.com/SanDiegoMachineLearning/bookclub Location This will be an online meetup until further notice. Questions? Join our slack channel or leave a comment below if you have any questions about the group or need clarification on anything. https://join.slack.com/t/sdmachinelearning/shared_invite/zt-6b0ojqdz-9bG7tyJMddVHZ3Zm9IajJA