Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python

Buy
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.

What You'll Learn
  • 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
Who This Book Is For


Data scientists, machine and deep learning engineers.

 
(HTML tags aren't allowed.)

Introduction to Computational Genomics: A Case Studies Approach
Introduction to Computational Genomics: A Case Studies Approach
Where did SARS come from? Have we inherited genes from Neanderthals? How do plants use their internal clock? The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many...
Elliptic Curves: Number Theory and Cryptography, Second Edition (Discrete Mathematics and Its Applications)
Elliptic Curves: Number Theory and Cryptography, Second Edition (Discrete Mathematics and Its Applications)
Over the last two or three decades, elliptic curves have been playing an increasingly important role both in number theory and in related fields such as cryptography. For example, in the 1980s, elliptic curves started being used in cryptography and elliptic curve techniques were developed for factorization and primality...
An Introduction to Tensors and Group Theory for Physicists
An Introduction to Tensors and Group Theory for Physicists

The second edition of this highly praised textbook provides an introduction to tensors, group theory, and their applications in classical and quantum physics. Both intuitive and rigorous, it aims to demystify tensors by giving the slightly more abstract but conceptually much clearer definition found in the math literature, and then connects...


Data Mining for Bioinformatics
Data Mining for Bioinformatics

Covering theory, algorithms, and methodologies, as well as data mining technologies, Data Mining for Bioinformatics provides a comprehensive discussion of data-intensive computations used in data mining with applications in bioinformatics. It supplies a broad, yet in-depth, overview of the application domains of data mining...

Ethereum Projects for Beginners: Build blockchain-based cryptocurrencies, smart contracts, and DApps
Ethereum Projects for Beginners: Build blockchain-based cryptocurrencies, smart contracts, and DApps

Understand the Ethereum platform to build distributed applications that are secured and decentralized using blockchain technology

Key Features

  • Build your own decentralized applications using real-world blockchain examples
  • Implement Ethereum for building smart contracts and...
Become a Python Data Analyst: Perform exploratory data analysis and gain insight into scientific computing using Python
Become a Python Data Analyst: Perform exploratory data analysis and gain insight into scientific computing using Python

Enhance your data analysis and predictive modeling skills using popular Python tools

Key Features

  • Cover all fundamental libraries for operation and manipulation of Python for data analysis
  • Implement real-world datasets to perform predictive analytics with Python
  • ...
©2020 LearnIT (support@pdfchm.net) - Privacy Policy