<div><div><font face="Noto Sans, sans-serif" size="2">Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning fra
Deep Learning with Python. A Hands-on Introduction
β Scribed by Nikhil Ketkar
- Publisher
- Apress
- Year
- 2017
- Tongue
- English
- Leaves
- 164
- Category
- Library
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Chapter 1: An intuitive look at the fundamentals of deep learning based on practical applications -- Chapter 2: A survey of the current state-of-the-art implementations of libraries, tools and packages for deep learning and the case for the Python ecosystem -- Chapter 3: A detailed look at Keras [1]
<p>Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The pract
Understand basic-to-advanced deep learning algorithms, the mathematical principles behind them, and their practical applications Key Features Get up to speed with building your own neural networks from scratch Gain insights into the mathematical principles behind deep learning algorithms Implement p
My goal here is for something that is partly a tutorial and partly a reference book. I like how tutorials get you up and running quickly, but they can often be a little wordy and disorganized. Reference books contain a lot of good information, but they are often too terse, and they donβt often give
This friendly and accessible guide to AI theory and programming in Python requires no maths or data science background. Key Features Roll up your sleeves and start programming AI models No math, data science, or machine learning background required Packed with hands-on examples, illustrations, and c