From 72a5466408a01ac0d43ab60138d107e9e589d446 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aur=C3=A9lien=20Geron?= Date: Thu, 20 Oct 2022 18:58:10 +1300 Subject: [PATCH] Clarify which sections are now online --- CHANGES.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/CHANGES.md b/CHANGES.md index 406a6d8..c9f5e84 100644 --- a/CHANGES.md +++ b/CHANGES.md @@ -8,4 +8,4 @@ Below are the changes in the book between the second (2019) and the third editio * Chapter 16 on natural language processing now builds an English-to-Spanish translation model, first using an encoder–decoder RNN, then using a transformer model. The chapter also covers language models such as Switch Transformers, DistilBERT, T5, and PaLM (with chain-of-thought prompting). In addition, it introduces vision transformers (ViTs) and gives an overview of a few transformer-based visual models, such as data-efficient image transformers (DeiTs), Perceiver, and DINO, as well as a brief overview of some large multimodal models, including CLIP, DALL·E, Flamingo, and GATO. * Chapter 17 on generative learning now introduces diffusion models, and shows how to implement a denoising diffusion probabilistic model (DDPM) from scratch. * Chapter 19 migrated from Google Cloud AI Platform to Google Vertex AI, and uses distributed Keras Tuner for large-scale hyperparameter search. The chapter now includes TensorFlow.js code that you can experiment with online. It also introduces additional distributed training techniques, including PipeDream and Pathways. -* To allow for all the new content, some sections are being moved online (should be available by December), including installation instructions, kernel principal component analysis (KPCA), mathematical details of Bayesian Gaussian mixtures, TF Agents, and former appendices A (exercise solutions), C (support vector machine math), and E (extra neural net architectures). +* To allow for all the new content, some sections have been moved online, including [installation instructions](INSTALL.md), and appendix A (the exercise solutions, now available at the end of each notebook). Other sections have been removed and will be added to this repository within the next few weeks, including kernel principal component analysis (kPCA), mathematical details of Bayesian Gaussian mixtures, TF Agents, and former appendices C (support vector machine math), and E (extra neural net architectures).