عنوان

Learn TensorFlow 2.0 :

شابک

1484255585

شابک

9781484255582

شابک اشتباه

9781484255575

عنوان اصلي

Learn TensorFlow 2.0 :

نام عام مواد

[Book]

ساير اطلاعات عنواني

implement machine learning and deep learning models with Python /

نام نخستين پديدآور

Pramod Singh, Avinash Manure.

محل نشرو پخش و غیره

Berkeley, CA :

نام ناشر، پخش کننده و غيره

Apress L.P.,

تاریخ نشرو بخش و غیره

©2020.

نام خاص و کميت اثر

1 online resource (177 pages)

متن يادداشت

Includes index.

متن يادداشت

Intro -- Table of Contents -- About the Authors -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Chapter 1: Introduction to TensorFlow 2.0 -- Tensor + Flow = TensorFlow -- Components and Basis Vectors -- Tensor -- Rank -- Shape -- Flow -- TensorFlow 1.0 vs. TensorFlow 2.0 -- Usability-Related Changes -- Simpler APIs -- High-Level APIs -- Lower-Level APIs -- Session Execution -- Eager Execution -- tf.function -- Keras -- Redundancy -- Improved Documentation and More Inbuilt Data Sources -- Performance-Related Changes -- Installation and Basic Operations in TensorFlow 2.0

متن يادداشت

Anaconda -- Colab -- Databricks -- Conclusion -- Chapter 2: Supervised Learning with TensorFlow -- What Is Supervised Machine Learning? -- Linear Regression with TensorFlow 2.0 -- Implementation of a Linear Regression Model, Using TensorFlow and Keras -- Logistic Regression with TensorFlow 2.0 -- Boosted Trees with TensorFlow 2.0 -- Ensemble Technique -- Bagging -- Boosting -- Gradient Boosting -- Conclusion -- Chapter 3: Neural Networks and Deep Learning with TensorFlow -- What Are Neural Networks? -- Neurons -- Artificial Neural Networks (ANNs) -- Simple Neural Network Architecture

متن يادداشت

Applications of Autoencoders -- Variational Autoencoders -- Implementation of Variational Autoencoders Using TensorFlow 2.0 -- Conclusion -- Chapter 5: Natural Language Processing with TensorFlow 2.0 -- NLP Overview -- Text Preprocessing -- Tokenization -- Word Embeddings -- Text Classification Using TensorFlow -- Text Processing -- Deep Learning Model -- Embeddings -- TensorFlow Projector -- Conclusion -- Chapter 6: TensorFlow Models in Production -- Model Deployment -- Isolation -- Collaboration -- Model Updates -- Model Performance -- Load Balancer -- Python-Based Model Deployment

متن يادداشت

Forward and Backward Propagation -- Building Neural Networks with TensorFlow 2.0 -- About the Data Set -- Deep Neural Networks (DNNs) -- Building DNNs with TensorFlow 2.0 -- Estimators Using the Keras Model -- Conclusion -- Chapter 4: Images with TensorFlow -- Image Processing -- Convolutional Neural Networks -- Convolutional Layer -- Pooling Layer -- Fully Connected Layer -- ConvNets Using TensorFlow 2.0 -- Advanced Convolutional Neural Network Architectures -- Transfer Learning -- Transfer Learning and Machine Learning -- Variational Autoencoders Using TensorFlow 2.0 -- Autoencoders

متن يادداشت

Saving and Restoring a Machine Learning Model -- Deploying a Machine Learning Model As a REST Service -- Templates -- Challenges of Using Flask -- Building a Keras TensorFlow-Based Model -- TF ind deployment -- Conclusion -- Index

بدون عنوان

0

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

متن يادداشت

Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0. It also demonstrates how to build models using customer estimators. Further, it explains how to use TensorFlow 2.0 API to build machine learning and deep learning models for image classification using the standard as well as custom parameters. You'll review sequence predictions, saving, serving, deploying, and standardized datasets, and then deploy these models to production. All the code presented in the book will be available in the form of executable scripts at Github which allows you to try out the examples and extend them in interesting ways. You will: Review the new features of TensorFlow 2.0 Use TensorFlow 2.0 to build machine learning and deep learning models Perform sequence predictions using TensorFlow 2.0 Deploy TensorFlow 2.0 models with practical examples.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9781484255582

عنوان

Learn TensorFlow 2. 0 : Implement Machine Learning and Deep Learning Models with Python.

شماره استاندارد بين المللي کتاب و موسيقي

9781484255605

موضوع مستند نشده

TensorFlow.

موضوع مستند نشده

Machine learning.

موضوع مستند نشده

Machine learning.

شماره

ويراست

شماره رده

مستند نام اشخاص تاييد نشده

Singh, Pramod.

مستند نام اشخاص تاييد نشده

Manure, Avinash.

تاريخ عمليات

20200823032923.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y