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)

Applications

Today, RNNs (for example, LSTM) have been used in a variety of different applications ranging from time series data modeling, image classification, and video captioning, as well as textual analysis. In this section, we will cover some important applications of RNNs for solving different natural language understanding problems.

Language modeling

Language modeling is one of the fundamental problems in natural language understanding (NLU). The core idea of a language model is to model important distributional properties of the words in a given language. Once such a model is learnt, it can be applied to a sequence of new words to generate the most likely next word token given the learned distributional representation...