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. In this blog post, you will be able to download free PDF e-book copy of Deep Learning with Python PDF.
The practicalities of these frameworks is often acquired by practitioners by reading source code, manuals, and posting questions on community forums, which tends to be a slow and a painful process. Deep Learning with Python allows you to ramp up to such practical know-how in a short period of time and focus more on the domain, models, and algorithms.
This book briefly covers the mathematical prerequisites and fundamentals of deep learning, making this book a good starting point for software developers who want to get started in deep learning. A brief survey of deep learning architectures is also included.
Deep Learning with Python also introduces you to key concepts of automatic differentiation and GPU computation which, while not central to deep learning, are critical when it comes to conducting large scale experiments.
Features of Deep Learning with Python PDF
Here are important features of this book:
- Leverage deep learning frameworks in Python namely, Keras, Theano, and Caffe
- Gain the fundamentals of deep learning with mathematical prerequisites
- Discover the practical considerations of large scale experiments
- Take deep learning models to production
Who This Book Is For?
Software developers who want to try out deep learning as a practical solution to a particular problem. Software developers in a data science team who want to take deep learning models developed by data scientists to production.
Table of Contents
Below is the complete table of contents presented in Deep Learning with Python PDF:
Chapter 1: Introduction to Deep Learning
Chapter 2: Machine Learning Fundamentals
Chapter 3: Feed Forward Neural Networks
Chapter 4: Introduction to Theano
Chapter 5: Convolutional Neural Networks
Chapter 6: Recurrent Neural Networks
Chapter 7: Introduction to Keras
Chapter 8: Stochastic Gradient Descent
Chapter 9: Automatic Differentiation
Chapter 10: Introduction to GPUs
Below are the technical specifications of Deep Learning with Python PDF.
- Book Name : Deep Learning with Python: A Hands-on Introduction
- Edition : 1st Edition | | ISBN : 1484227654
- Author Name : Nikhil Ketkar
- Category : Programming
- Format / Pages : PDF – 169 Pages
Deep Learning with Python PDF Free Download
Here you will be able to download Deep Learning with Python PDF by using our direct download links that have been mentioned at the end of this article. This is a genuine PDF e-book file. We hope that you find this book useful in your studies. 🙂
Below is a screenshot of the cover image of this book:
FILE SIZE: 7.44 MB
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Happy learning, folks! 🙂
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