Deep Learning For Dummies

Häftad, Engelska, 2019

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Take a deep dive into deep learning Deep learning provides the means for discerning patterns in the data that drive online business and social media outlets. Deep Learning for Dummies gives you the information you need to take the mystery out of the topic—and all of the underlying technologies associated with it. In no time, you’ll make sense of those increasingly confusing algorithms, and find a simple and safe environment to experiment with deep learning. The book develops a sense of precisely what deep learning can do at a high level and then provides examples of the major deep learning application types. Includes sample codeProvides real-world examples within the approachable textOffers hands-on activities to make learning easierShows you how to use Deep Learning more effectively with the right toolsThis book is perfect for those who want to better understand the basis of the underlying technologies that we use each and every day.

Produktinformation

Utgivningsdatum2019-06-14
Mått185 x 234 x 23 mm
Vikt499 g
FormatHäftad
SpråkEngelska
Antal sidor368
FörlagJohn Wiley & Sons Inc
ISBN9781119543046

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John Paul Mueller is the author of over 100 books including AI for Dummies, Python for Data Science for Dummies, Machine Learning for Dummies, and Algorithms for Dummies. Luca Massaron is a data scientist who interprets big data and transforms it into smart data by means of the simplest and most effective data mining and machine learning techniques. He is a Google Developer Expert (GDE) in machine learning.

Introduction 1Part 1: Discovering Deep Learning 7Chapter 1: Introducing Deep Learning 9Chapter 2: Introducing the Machine Learning Principles 25Chapter 3: Getting and Using Python 45Chapter 4: Leveraging a Deep Learning Framework 73Part 2: Considering Deep Learning Basics 91Chapter 5: Reviewing Matrix Math and Optimization 93Chapter 6: Laying Linear Regression Foundations 111Chapter 7: Introducing Neural Networks 131Chapter 8: Building a Basic Neural Network 149Chapter 9: Moving to Deep Learning 163Chapter 10: Explaining Convolutional Neural Networks 179Chapter 11: Introducing Recurrent Neural Networks 201Part 3: Interacting with Deep Learning 215Chapter 12: Performing Image Classification 217Chapter 13: Learning Advanced CNNs 233Chapter 14: Working on Language Processing 251Chapter 15: Generating Music and Visual Art 269Chapter 16: Building Generative Adversarial Networks 279Chapter 17: Playing with Deep Reinforcement Learning 293Part 4: The Part of Tens 307Chapter 18: Ten Applications that Require Deep Learning 309Chapter 19: Ten Must-Have Deep Learning Tools 317Chapter 20: Ten Types of Occupations that Use Deep Learning 327Index 335