Tensorflow Machine Learning Projects

Download Tensorflow Machine Learning Projects full books in PDF, epub, and Kindle. Read online free Tensorflow Machine Learning Projects ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!


Related Books

TensorFlow Machine Learning Projects
Language: en
Pages: 311
Authors: Ankit Jain
Categories: Computers
Type: BOOK - Published: 2018-11-30 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Implement TensorFlow's offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and TensorFlow Lite to build smart automation projects Key Features
TensorFlow Deep Learning Projects
Language: en
Pages: 310
Authors: Alexey Grigorev
Categories: Computers
Type: BOOK - Published: 2018-03-28 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios Key Features Build efficient deep learning pipelines usin
Deep Learning Projects Using TensorFlow 2
Language: en
Pages: 421
Authors: Vinita Silaparasetty
Categories: Computers
Type: BOOK - Published: 2020-08-08 - Publisher: Apress

DOWNLOAD EBOOK

Work through engaging and practical deep learning projects using TensorFlow 2.0. Using a hands-on approach, the projects in this book will lead new programmers
Machine Learning Projects for Mobile Applications
Language: en
Pages: 240
Authors: Karthikeyan NG
Categories: Computers
Type: BOOK - Published: 2018-10-31 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Bring magic to your mobile apps using TensorFlow Lite and Core ML Key FeaturesExplore machine learning using classification, analytics, and detection tasks.Work
Machine Learning with TensorFlow, Second Edition
Language: en
Pages: 454
Authors: Mattmann A. Chris
Categories: Computers
Type: BOOK - Published: 2021-02-02 - Publisher: Manning

DOWNLOAD EBOOK

Updated with new code, new projects, and new chapters, Machine Learning with TensorFlow, Second Edition gives readers a solid foundation in machine-learning con