Book

Deep Learning By Example

Deep Learning is a subset of Machine Learning and has gained a lot of popularity recently. This book introduces you to the fundamentals of deep learning in a hands-on manner. You will use Tensorflow to train different types of neural networks for tasks related to computer vision, language processing, and other real-world problems.

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Difficulty Level

Intermediate

Completion Time

15h

Language

English

About Book

Who Is This Book For?

This book targets data scientists and machine learning developers who wish to get started with deep learning. If you know what deep learning is but are not quite sure of how to use it, this book will help you as well. An understanding of statistics and data science concepts is required. Some familiarity with Python programming will also be beneficial.

Book content

chapters 15h total length

Data science: Bird's-eye view

Data Modeling in Action - The Titanic Example

Feature Engineering and Model Complexity – The Titanic Example Revisited

Get Up and Running with TensorFlow

Tensorflow in Action - Some Basic Examples

Deep Feed-forward Neural Networks - Implementing Digit Classification

Introduction to Convolutional Neural Networks

Object Detection – CIFAR-10 Example

Object Detection – Transfer Learning with CNNs

Recurrent-Type Neural Networks - Language modeling

Representation Learning - Implementing Word Embeddings

Neural sentiment Analysis

Autoencoders – Feature Extraction and Denoising

Generative Adversarial Networks in Action - Generating New Images

Face Generation and Handling Missing Labels

Appendix - Implementing Fish Recognition

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