Book Abstract: Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability teaches the increasingly popular probabilistic approach to deep learning that allows you to refine your ...

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book ...

Most deep learning books are based on one of several popular Python libraries such as TensorFlow, PyTorch, or Keras. In contrast, Grokking Deep Learning teaches you deep learning by building ...

What is this book about? Keras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and ...

Some of the most popular Python libraries for deep learning include TensorFlow, PyTorch, NumPy, Sci-kit Learn, and Keras. Each library provides unique features tailored toward different ...

Keras proper, a high-level front end for building neural network models, ships with support for three back-end deep learning frameworks ... Both expose Python APIs. There are some practical ...

Python has a wealth of scientific ... the recommendation for how to choose a deep learning library: If you’re brand new to deep learning, consider Keras, followed by PyTorch.

A lot of software developers are drawn to Python ... Keras is a popular open-source neural network library for the development and evaluation of neural networks within machine learning and deep ...

This book is aimed at intermediate machine learning engineers, software engineers, technology architects and programmers who are interested in knowing more about deep learning, especially applied deep ...