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TensorFlow machine learning cookbook : explore machine learning concepts using the latest numerical computing library, TensorFlow, with the help of this comprehenisive cookbook /
TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You'll work through recipes on trai...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham, UK :
Packt Publishing,
2017.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
| LEADER | 00000cam a2200000Ii 4500 | ||
|---|---|---|---|
| 001 | OR_ocn974929461 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o d | ||
| 007 | cr unu|||||||| | ||
| 007 | cr cnu---unuuu | ||
| 008 | 170309s2017 enka o 001 0 eng d | ||
| 040 | |a UMI |b eng |e rda |e pn |c UMI |d OCLCF |d STF |d IDEBK |d OCLCQ |d ALAUL |d CEF |d KSU |d DEBBG |d UAB |d OCLCO |d OCLCQ |d OCLCO | ||
| 020 | |z 9781786462169 |q (electronic) | ||
| 020 | |a 9781786466303 | ||
| 020 | |a 1786466309 | ||
| 029 | 1 | |a GBVCP |b 897169638 | |
| 035 | |a (OCoLC)974929461 | ||
| 037 | |a CL0500000837 |b Safari Books Online | ||
| 050 | 4 | |a Q325.5 |b .M335 2017eb | |
| 082 | 0 | 4 | |a 006.3 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a McClure, Nick, |e author. | |
| 245 | 1 | 0 | |a TensorFlow machine learning cookbook : |b explore machine learning concepts using the latest numerical computing library, TensorFlow, with the help of this comprehenisive cookbook / |c Nick McClure. |
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2017. | |
| 300 | |a 1 online resource (370 pages): |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | |a Description based on online resource; title from cover (Safari, viewed March 7, 2017). | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Cover; Copyright; Credits; About the Author; About the Reviewer; www.PacktPub.com; Customer Feedback; Table of Contents; Preface; Chapter 1: Getting Started with TensorFlow; Introduction; How TensorFlow Works; Declaring Tensors; Using Placeholders and Variables; Working with Matrices; Declaring Operations; Implementing Activation Functions; Working with Data Sources; Additional Resources; Chapter 2: The TensorFlow Way; Introduction; Operations in a Computational Graph; Layering Nested Operations; Working with Multiple Layers; Implementing Loss Functions; Implementing Back Propagation. Working with Batch and Stochastic TrainingCombining Everything Together; Evaluating Models; Chapter 3: Linear Regression; Introduction; Using the Matrix Inverse Method; Implementing a Decomposition Method; Learning The TensorFlow Way of Linear Regression; Understanding Loss Functions in Linear Regression; Implementing Deming regression; Implementing Lasso and Ridge Regression; Implementing Elastic Net Regression; Implementing Logistic Regression; Chapter 4: Support Vector Machines; Introduction; Working with a Linear SVM; Reduction to Linear Regression; Working with Kernels in TensorFlow -- Implementing a Non-Linear SVMImplementing a Multi-Class SVM; Chapter 5: Nearest Neighbor Methods; Introduction; Working with Nearest Neighbors; Working with Text-Based Distances; Computing with Mixed Distance Functions; Using an Address Matching Example; Using Nearest Neighbors for Image Recognition; Chapter 6: Neural Networks; Introduction; Implementing Operational Gates; Working with Gates and Activation Functions; Implementing a One-Layer Neural Network; Implementing Different Layers; Using a Multilayer Neural Network; Improving the Predictions of Linear Models -- Stacking multiple LSTM LayersCreating Sequence-to-Sequence Models; Training a Siamese Similarity Measure; Chapter 10: Taking TensorFlow to Production; Introduction; Implementing unit tests; Using Multiple Executors; Parallelizing TensorFlow; Taking TensorFlow to Production; Productionalizing TensorFlow -- An Example; Chapter 11: More with TensorFlow; Introduction; Visualizing graphs in Tensorboard; There's more ... ; Working with a Genetic Algorithm; Clustering Using K-Means; Solving a System of ODEs | |
| 520 | |a TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You'll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning - each using Google's machine learning library TensorFlow. This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Intelligence artificielle. | |
| 650 | 7 | |a artificial intelligence. |2 aat | |
| 650 | 7 | |a Artificial intelligence |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781786462169/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 938 | |a ProQuest MyiLibrary Digital eBook Collection |b IDEB |n cis35312900 | ||
| 994 | |a 92 |b IZTAP | ||