John Paul Mueller, Luca Massaron

Deep Learning For Dummies (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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 code * Provides real-world examples within the approachable text * Offers hands-on activities to make learning easier * Shows you how to use Deep Learning more effectively with the right tools This book is perfect for those who want to better understand the basis of the underlying technologies that we use each and every day.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: For Dummies
• Seitenzahl: 368
• Erscheinungstermin: 17. April 2019
• Englisch
• ISBN-13: 9781119543039
• Artikelnr.: 56523986

Autorenporträt

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.

Inhaltsangabe

Introduction 1

Part 1: Discovering Deep Learning 7

Chapter 1: Introducing Deep Learning 9

Chapter 2: Introducing the Machine Learning Principles 25

Chapter 3: Getting and Using Python 45

Chapter 4: Leveraging a Deep Learning Framework 73

Part 2: Considering Deep Learning Basics 91

Chapter 5: Reviewing Matrix Math and Optimization 93

Chapter 6: Laying Linear Regression Foundations 111

Chapter 7: Introducing Neural Networks 131

Chapter 8: Building a Basic Neural Network 149

Chapter 9: Moving to Deep Learning 163

Chapter 10: Explaining Convolutional Neural Networks 179

Chapter 11: Introducing Recurrent Neural Networks 201

Part 3: Interacting with Deep Learning 215

Chapter 12: Performing Image Classification 217

Chapter 13: Learning Advanced CNNs 233

Chapter 14: Working on Language Processing 251

Chapter 15: Generating Music and Visual Art 269

Chapter 16: Building Generative Adversarial Networks 279

Chapter 17: Playing with Deep Reinforcement Learning 293

Part 4: The Part of Tens 307

Chapter 18: Ten Applications that Require Deep Learning 309

Chapter 19: Ten Must-Have Deep Learning Tools 317

Chapter 20: Ten Types of Occupations that Use Deep Learning 327

Index 335