Deep Learning for Programmers (460 pages)
The 2nd edition available!
aren’t these surfers adorable? the book is too!
or scroll down to read the pitch, download sample chapters,
Open Source Libraries
Why?
basically…
this is the only DL book for programmers
interactive & dynamic
step-by-step implementation
incredible performance, yet no C++ hell (!)
Intel & AMD CPUs (DNNL)
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 below)
No Middleman
no middleman!
100% of the revenue goes towards my open-source work!
For Programmers
the only AI book that walks the walk
complete, 100% executable code
step-by-step instructions
full path from theory to implementation in actual code
superfast implementation
Other books are math-only monographs for academics, or are written for non-technical readers.
Deep Learning
learn DL by implementing it from scratch
classic neural networks using fast linear algebra
build an optimized backpropagation algorithm step-by-step
explore it on the CPU
run it on the GPU!
design an elegant neural network API
add tensor support
integrate with Intel’s DNNL and Nvidia’s cuDNN performance libraries
learn the nuts and bolts
build convolutional layers
build RNN support
understand how to use it to solve practical problems
…and much more!
Interactive
immediate dynamic feedback
see the result of executing each line
experiment in a live environment
no C++ build hell
no C++ syntax hell!
Java Virtual Machine, but without Java boilerplate
Clojure, the nicest language on earth :-)
no C++ at all!!!
Fast
optimized
yet, high-level (you don’t touch C++)
CPUs
learn Intel DNNL
GPUs
learn CUDA & cuDNN
learn OpenCL
all hardware: Nvidia, AMD, Intel
you don’t touch C++!!!
buy
buy now and read the full book.
get the current edition as PDF + code.
subscribe for early access to the updates and drafts of the next edition.
get new chapters and updates of the 2nd edition as soon as they are ready
all revenue goes towards funding my work on the open source libraries used in the book
your name in the book’s acknowledgments
get the book and help make it awesome!
Contents
Table of Contents
Part 1: Getting Started
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)
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)
Initializing weights (AVAILABLE)
Regression: learning a known function (AVAILABLE)
Part 5: Training optimizations (AVAILABLE)
Momentum and Nesterov momentum (AVAILABLE)
Adaptive learning rates (AVAILABLE)
Regression: Boston housing prices (AVAILABLE)
Stochastic gradient descent (AVAILABLE)
Classification: IMDB sentiments (AVAILABLE)
Classification and metrics: MNIST handwritten digits recognition (AVAILABLE)
Tensors and ND arrays (AVAILABLE)
Tensor transformations (AVAILABLE)
DNNL: Tensors on the CPU (AVAILABLE)
Tensor-based neural networks (AVAILABLE)
cuDNN: Tensors on the GPU (AVAILABLE)
Part 7: Convolutional networks (AVAILABLE)
The convolution operation (AVAILABLE)
Convolutional layers on the CPU with DNNL (AVAILABLE)
Convolutional neural networks (CNN): Fashion-MNIST (AVAILABLE)
CNN on the GPU with cuDNNL (AVAILABLE)
Part 8: Recurrent neural networks (IN PRORESS)
Recurrent layers (AVAILABLE)
Recurrent neural networks (RNN) (AVAILABLE)
Recurrent layers on the CPU with DNNL (AVAILABLE)
Recurrent layers on the GPU with cuDNN (AVAILABLE)
(Future editions, TBD)
Appendix
Setting up the environment and the JVM (AVAILABLE)
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get new chapters as they are written
all revenue goes towards funding my work on the open source libraries used in the book
your name in the book’s acknowledgments
special copy with a personalized thank you note
personalized handcrafted hardcovers for chapter sponsors
get in early and help make this book awesome!
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