New release:Deep Learning for Programmers: An Interactive Tutorial with CUDA, OpenCL, MKL-DNN, Java, and Clojure
https://aiprobook.com/deep-learning-for-programmers <https://aiprobook.com/deep-learning-for-programmers?release=0.11.0&source=cgroups> + Chapter on Adaptive Learning Rates ** no middleman! 100% of the revenue goes towards my open-source work! ** this is the only DL book for programmers - interactive & dynamic - step-by-step implementation - incredible performance, yet no C++ hell (!) - Intel & AMD CPUs (MKL-DNN) - Nvidia GPUs (CUDA and cuDNN) - AMD GPUs (yes, OpenCL too!) - Clojure (it’s magic!) - Java Virtual Machine (without Java boilerplate!) - complete source code - beautiful typesetting (see the sample chapters) Current status: ## Table of Contents ### Part 1: Getting Started 4-6 chapters, (TO BE DETERMINED) ### Part 2: Inference ([AVAILABLE]) #### Representing layers and connections ([AVAILABLE]) #### Bias and activation function ([AVAILABLE]) #### Fully connected inference layers ([AVAILABLE]) #### Increasing performance with batch processing ([AVAILABLE]) #### Sharing memory ([AVAILABLE]) #### GPU computing with CUDA and OpenCL ([AVAILABLE] ### Part 3: Learning ([AVAILABLE] #### Gradient descent and backpropagation ([AVAILABLE] #### The forward pass ([AVAILABLE] #### The activation and its derivative ([AVAILABLE] #### The backward pass ([AVAILABLE] ### Part 4: A simple neural networks API ([AVAILABLE] #### Inference API ([AVAILABLE] #### Training API ([AVAILABLE] #### Initializing weights ([AVAILABLE] #### Regression: learning a known function ([AVAILABLE] ### Part 5: Training optimizations (IN PROGSESS) #### Weight decay ([AVAILABLE] #### Momentum and Nesterov momentum ([AVAILABLE] #### Adaptive learning rates ([AVAILABLE] #### Regression: Boston housing prices (SOON) #### Dropout (SOON) #### Stochastic gradient descent (SOON) #### Classification: IMDB sentiments (SOON) ### Part 6: Tensors (TO BE DETERMINED, BUT SOON ENOUGH) #### Tensors, Matrices, and ND-arrays (TBD) #### Tensors on the CPU with MKL-DNN (TBD) #### Tensors on the GPU with cuDNN (TBD) #### Tensor API (TBD) ### Part 7: Convolutional layers (TBD) 4-6 Chapters, (TBD) ### Part 8: Recurrent networks (TBD) 4-6 Chapters, (TBD) -- You received this message because you are subscribed to the Google Groups "Clojure" group. To post to this group, send email to clojure@googlegroups.com Note that posts from new members are moderated - please be patient with your first post. To unsubscribe from this group, send email to clojure+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/clojure?hl=en --- You received this message because you are subscribed to the Google Groups "Clojure" group. To unsubscribe from this group and stop receiving emails from it, send an email to clojure+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/clojure/870a0b12-bdcd-4e0a-aecf-1dc14ad88c32%40googlegroups.com.
