In Coding the Deep Learning Revolution – a step by step introduction using Python, TensorFlow and Keras you’ll be getting a head start on your deep learning journey. This book has been written to provide readers with a thorough and practical guide to the fundamental concepts and architectures of deep learning, using Python and the most popular deep learning frameworks – TensorFlow and Keras. Here’s what you’ll learn about:
- What is deep learning? It’s history and hurdles
- Tensors and computational graphs
- TensorFlow variables, operations, optimizers and more
- TensorBoard visualization
- The vanishing gradient problem and activation functions
- Network optimization including proper weight initialization
- Convolutional Neural Network architectures
- Using CNNs to perform image classification on the CIFAR-10 dataset
- The TensorFlow Dataset API for efficient data consumption and high performing networks
- An introduction to Keras, including the Sequential and Functional APIs
- Using the now tightly integrated Keras API in a TensorFlow environment
- Drop-out, weight regularization and batch normalization
- An introduction to word embeddings, Word2Vec and negative sampling
- Recurrent neural networks, their advantages and deficiencies
- LSTM cells and their use in natural language processing on a real text dataset example
- and more…
Unsure of what some of these terms mean, or worried you’re a novice? Don’t worry, you can couple this book with my free 40 page beginners neural networks eBook and you’ll have the full package.
For $19USD here is what you’ll get:
- A detailed yet clear, highly illustrated 106 page PDF eBook with step by step coding explanations and deep learning theory
- A package of fully functioning Python files which contain all the code examples explained within this book
- A lifetime of free updates of the book as TensorFlow and Keras progress to new versions (this is especially important for the upcoming release of TensorFlow 2.0!)
Make 2019 the year you become proficient in the skills, knowledge and tools required to participate in the deep learning revolution – click on the button below!
Not sure if the book will explain things very well? Here are some quotes from readers about my (Dr Andy Thomas’s) teaching style that might help:
This is really nice blog… the way you explained concepts with the help of elaborate diagrams and simple mathematical formulas is highly commendable.Yashodhan Pawar
This is the best self learning site I have ever came across for deep learning. It is so appreciable! I was finding it hard to read through the arguments on my own and relating it with the logic. You made it piece of cake!Prashant Brahmbhatt
Well done, this is outstanding work, many thanks for this article !
The same applies for the Keras article. Your tutorials are easy to follow and one can get familiar with the topic in an enjoyable way.
I’m excited to have released this book. My hope is that it will be a stepping stone for people eager to learn about this really exciting area of machine learning. Some experts predict large job losses due to advancements in artificial intelligence and deep learning within the next 5-10 years (up to 40%), so I’m hoping my book can assist readers in preparing for this change.
That’s the negative take – the positive is that studying deep learning and applying it in new and exciting ways is just lots of fun.
So if this sounds like something you’re interested in, click on the button below and start your deep learning journey.