Machine Learning With Tensorflow, Second Edition

Updated With New Code, New Projects, And New Chapters, Machine Learning With Tensorflow, Second Edition Gives Readers A Solid Foundation In Machine-Learning Concepts And The Tensorflow Library.Summaryupdated With New Code, New Projects, And New Chapters, Machine Learning With Tensorflow, Second Edition Gives Readers A Solid Foundation In Machine-Learning Concepts And The Tensorflow Library. Written By Nasa Jpl Deputy Cto And Principal Data Scientist Chris Mattmann, All Examples Are Accompanied By Downloadable Jupyter Notebooks For A Hands-On Experience Coding Tensorflow With Python. New And Revised Content Expands Coverage Of Core Machine Learning Algorithms, And Advancements In Neural Networks Such As Vgg-Face Facial Identification Classifiers And Deep Speech Classifiers.Purchase Of The Print Book Includes A Free Ebook In Pdf, Kindle, And Epub Formats From Manning Publications.About The Technologysupercharge Your Data Analysis With Machine Learning! Ml Algorithms Automatically Improve As They Process Data, So Results Get Better Over Time. You Don&;T Have To Be A Mathematician To Use Ml: Tools Like Google&;S Tensorflow Library Help With Complex Calculations So You Can Focus On Getting The Answers You Need.About The Bookmachine Learning With Tensorflow, Second Edition Is A Fully Revised Guide To Building Machine Learning Models Using Python And Tensorflow. You&;Ll Apply Core Ml Concepts To Real-World Challenges, Such As Sentiment Analysis, Text Classification, And Image Recognition. Hands-On Examples Illustrate Neural Network Techniques For Deep Speech Processing, Facial Identification, And Auto-Encoding With Cifar-10.WhatS Insidemachine Learning With Tensorflowchoosing The Best Ml Approachesvisualizing Algorithms With Tensorboardsharing Results With Collaboratorsrunning Models In Dockerabout The Readerrequires Intermediate Python Skills And Knowledge Of General Algebraic Concepts Like Vectors And Matrices. Examples Use The Super-Stable 1.15.X Branch Of Tensorflow And Tensorflow 2.X.About The Authorchris Mattmann Is The Division Manager Of The Artificial Intelligence, Analytics, And Innovation Organization At Nasa Jet Propulsion Lab. The First Edition Of This Book Was Written By Nishant Shukla With Kenneth Fricklas.Table Of Contentspart 1 - Your Machine-Learning Rig1 A Machine-Learning Odyssey2 Tensorflow Essentialspart 2 - Core Learning Algorithms3 Linear Regression And Beyond4 Using Regression For Call-Center Volume Prediction5 A Gentle Introduction To Classification6 Sentiment Classification: Large Movie-Review Dataset7 Automatically Clustering Data8 Inferring User Activity From Android Accelerometer Data9 Hidden Markov Models10 Part-Of-Speech Tagging And Word-Sense Disambiguationpart 3 - The Neural Network Paradigm11 A Peek Into Autoencoders12 Applying Autoencoders: The Cifar-10 Image Dataset13 Reinforcement Learning14 Convolutional Neural Networks15 Building A Real-World Cnn: Vgg-Face Ad Vgg-Face Lite16 Recurrent Neural Networks17 Lstms And Automatic Speech Recognition18 Sequence-To-Sequence Models For Chatbots19 Utility Landscape