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Deep Learning Quick Re... von Bernico, Michael Digital (elektronisch geliefert)-
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eBay-Artikelnr.:305515974187
Artikelmerkmale
- Artikelzustand
- ISBN
- 1788837991
- EAN
- 9781788837996
- Date of Publication
- 2023-04-02
- Release Title
- Deep Learning Quick Reference
- Artist
- Bernico, Michael
- Brand
- N/A
- Colour
- N/A
- Book Title
- Deep Learning Quick Reference
Über dieses Produkt
Product Identifiers
Publisher
Packt Publishing, The Limited
ISBN-10
1788837991
ISBN-13
9781788837996
eBay Product ID (ePID)
3038498970
Product Key Features
Number of Pages
272 Pages
Publication Name
Deep Learning Quick Reference : Useful Hacks for Training and Optimizing Deep Neural Networks with TensorFlow and Keras
Language
English
Publication Year
2018
Subject
Machine Theory, Intelligence (Ai) & Semantics, Neural Networks, Data Processing
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Length
3.6 in
Item Width
3 in
Additional Product Features
Intended Audience
Trade
Table Of Content
Table of Contents The Building Blocks of Deep Learning Using Deep Learning To Solve Regression Problems Monitoring Network Training Using Tensor Board Using Deep Learning To Solve Binary Classification Problems Using Keras To Solve MultiClass Classification Problems HyperParameter Optimization Training a CNN From Scratch Transfer Learning with Pretrained CNNs Training an RNN from scratch Training LSTMs with Word Embeddings From Scratch Training Seq2Seq Models Using Deep Reinforcement Learning Deep Convolutional Generative Adversarial Networks
Synopsis
Dive deeper into neural networks and get your models trained, optimized with this quick reference guide Key Features A quick reference to all important deep learning concepts and their implementations Essential tips, tricks, and hacks to train a variety of deep learning models such as CNNs, RNNs, LSTMs, and more Supplemented with essential mathematics and theory, every chapter provides best practices and safe choices for training and fine-tuning your models in Keras and Tensorflow. Book Description Deep learning has become an essential necessity to enter the world of artificial intelligence. With this book deep learning techniques will become more accessible, practical, and relevant to practicing data scientists. It moves deep learning from academia to the real world through practical examples. You will learn how Tensor Board is used to monitor the training of deep neural networks and solve binary classification problems using deep learning. Readers will then learn to optimize hyperparameters in their deep learning models. The book then takes the readers through the practical implementation of training CNN's, RNN's, and LSTM's with word embeddings and seq2seq models from scratch. Later the book explores advanced topics such as Deep Q Network to solve an autonomous agent problem and how to use two adversarial networks to generate artificial images that appear real. For implementation purposes, we look at popular Python-based deep learning frameworks such as Keras and Tensorflow, Each chapter provides best practices and safe choices to help readers make the right decision while training deep neural networks. By the end of this book, you will be able to solve real-world problems quickly with deep neural networks. What you will learn Solve regression and classification challenges with TensorFlow and Keras Learn to use Tensor Board for monitoring neural networks and its training Optimize hyperparameters and safe choices/best practices Build CNN's, RNN's, and LSTM's and using word embedding from scratch Build and train seq2seq models for machine translation and chat applications. Understanding Deep Q networks and how to use one to solve an autonomous agent problem. Explore Deep Q Network and address autonomous agent challenges. Who this book is for If you are a Data Scientist or a Machine Learning expert, then this book is a very useful read in training your advanced machine learning and deep learning models. You can also refer this book if you are stuck in-between the neural network modeling and need immediate assistance in getting accomplishing the task smoothly. Some prior knowledge of Python and tight hold on the basics of machine learning is required., Dive deeper into neural networks and get your models trained, optimized with this quick reference guideAbout This Book* A quick reference to all important deep learning concepts and their implementations* Essential tips, tricks, and hacks to train a variety of deep learning models such as CNNs, RNNs, LSTMs, and more* Supplemented with essential mathematics and theory, every chapter provides best practices and safe choices for training and fine-tuning your models in Keras and Tensorflow.Who This Book Is ForIf you are a Data Scientist or a Machine Learning expert, then this book is a very useful read in training your advanced machine learning and deep learning models. You can also refer this book if you are stuck in-between the neural network modeling and need immediate assistance in getting accomplishing the task smoothly. Some prior knowledge of Python and tight hold on the basics of machine learning is required.What You Will Learn* Solve regression and classification challenges with TensorFlow and Keras* Learn to use Tensor Board for monitoring neural networks and its training* Optimize hyperparameters and safe choices/best practices* Build CNN's, RNN's, and LSTM's and using word embedding from scratch* Build and train seq2seq models for machine translation and chat applications.* Understanding Deep Q networks and how to use one to solve an autonomous agent problem.* Explore Deep Q Network and address autonomous agent challenges.In DetailDeep learning has become an essential necessity to enter the world of artificial intelligence. With this book deep learning techniques will become more accessible, practical, and relevant to practicing data scientists. It moves deep learning from academia to the real world through practical examples.You will learn how Tensor Board is used to monitor the training of deep neural networks and solve binary classification problems using deep learning. Readers will then learn to optimize hyperparameters in their deep learning models. The book then takes the readers through the practical implementation of training CNN's, RNN's, and LSTM's with word embeddings and seq2seq models from scratch. Later the book explores advanced topics such as Deep Q Network to solve an autonomous agent problem and how to use two adversarial networks to generate artificial images that appear real. For implementation purposes, we look at popular Python-based deep learning frameworks such as Keras and Tensorflow, Each chapter provides best practices and safe choices to help readers make the right decision while training deep neural networks.By the end of this book, you will be able to solve real-world problems quickly with deep neural networks.Style and approachAn easy-to-follow, step-by-step guide to help you get to grips with real-world applications of training deep neural networks., This book is a practical guide to applying deep neural networks including MLPs, CNNs, LSTMs, and more in Keras and TensorFlow. Packed with useful hacks to solve real-world challenges along with the supported math and theory around each topic, this book will be a quick reference for training and optimize your deep neural networks.
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- r***1 (40)- Bewertung vom Käufer.Letzter MonatBestätigter KaufPrices was great for the great condition. Something was up with the tracking, I couldn’t track the package. But customer service DID answer my question very quickly. I do wish the description had said there was previous gift writing on one of the pages. Not a problem for me but for some it would be and I think it’s only right to share that.
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World of Books USA
88,7% positive Bewertungen•5,2 Mio. Artikel verkauft
Angemeldet als gewerblicher Verkäufer
Verkäuferbewertungen (1.569.375)
- r***1 (40)- Bewertung vom Käufer.Letzter MonatBestätigter KaufPrices was great for the great condition. Something was up with the tracking, I couldn’t track the package. But customer service DID answer my question very quickly. I do wish the description had said there was previous gift writing on one of the pages. Not a problem for me but for some it would be and I think it’s only right to share that.
- m***m (126)- Bewertung vom Käufer.Letzter MonatBestätigter KaufThe quality and condition was better than expected. Definitely worth the value I bought it for. Will definitely buy from them in the future.
- _***i (1)- Bewertung vom Käufer.Letzter MonatBestätigter KaufExcelente condición. Entrega dentro del tiempo estimado.