Book Image

Deep Learning Essentials

By : Wei Di, Jianing Wei, Anurag Bhardwaj
3 (1)
Book Image

Deep Learning Essentials

3 (1)
By: Wei Di, Jianing Wei, Anurag Bhardwaj

Overview of this book

Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as CNN, RNN, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing using Python library such as TensorFlow. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, and small datasets. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications.
Table of Contents (12 chapters)

Tricks in training

In this section, we will talk about a few techniques that can help to train a better network, including how to initialize weights, tips for optimization parameters, and how to reduce overfitting.

Weight initialization

Following techniques are involved in weight initialization:

  • All-zero
  • Random initialization
  • ReLU initialization
  • Xavier initialization

All-zero

First, do NOT use all-zero initialization. Given proper data normalization, it is expected that roughly half of the network weights will be positive and half will be negative. However, this does...