Author: Matthew Lamons, Rahul Kumar and Abhishek Nagaraja
ISBN-13: 978-1-78899-709-6
Total Pages: 628
Size: 24.4MB
Description:
This book is perfect for you if you've undertaken at least one course in machine learning and have a modest functional proficiency in Python (meaning you can create programs in Python when supported by examples). Many of our readers will be undergraduates at university studying computer science, statistics, mathematics, physics, biology, chemistry, marketing, and business. Deep learning technologies are being applied to all the professions that these degrees prepare you for, and this book is a great way to learn skills that will be applicable to your success. Postgraduates will appreciate the instruction level, too, as the projects selected are directly applicable to the modern job market, from tech stat-ups to enterprise applications.
Table of Contents:
Chapter 1 - Building Deep Learning Environments
Chapter 2 - Training a Neural Net for Prediction Using Regression
Chapter 3 - Word Representations Using word2vec
Chapter 4 - Build a NLP Pipeline for Building Chatbots
Chapter 5 - Sequence to sequence Models for Building Chatbots
Chapter 6 - Generative Language Model for Content Creation
Chapter 7 - Building Speech Recognition with DeepSpeech2
Chapter 8 - Handwritten Digit Classification Using ConvNets
Chapter 9 - Object Detection Using OpenCV and TensorFlow
Chapter 10 - Building Facial Recognition Using FaceNet
Chapter 11 - Automated Image Captioning
Chapter 12 - Pose Estimation on 3D Models Using ConvNets
Chapter 13 - Image Translation Using GANs for Style Transfer
Chapter 14 - Develop an Autonomous Agent with Deep R Learning
Chapter 15 - Summary and Next Steps in Your Deep Learning Career