Machine Learning with TensorFlow 1.x: Second generation machine learning with Google's brainchild - TensorFlow 1.x

Cover
Copyright
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Table of Contents
Preface
Chapter 1: Getting Started with TensorFlow
	Current use
	Installing TensorFlow
		Ubuntu installation
		macOS installation
		Windows installation
		Virtual machine setup
		Testing the installation
	Summary
Chapter 2: Your First Classifier
	The key parts
	Obtaining training data
	Downloading training data
	Understanding classes
		Automating the training data setup
	Additional setup
		Converting images to matrices
	Logical stopping points
	The machine learning briefcase
	Training day
	Saving the model for ongoing use
	Why hide the test set?
	Using the classifier
	Deep diving into the network
	Skills learned
	Summary
Chapter 3: The TensorFlow Toolbox
	A quick preview
	Installing TensorBoard
		Incorporating hooks into our code
			Handwritten digits
		AlexNet
	Automating runs
	Summary
Chapter 4: Cats and Dogs
	Revisiting notMNIST
		Program configurations
		Understanding convolutional networks
		Revisiting configurations
		Constructing the convolutional network
		Fulfilment
	Training day
	Actual cats and dogs
	Saving the model for ongoing use
	Using the classifier
	Skills learned
	Summary
Chapter 5: Sequence to Sequence Models-Parlez-vous Français?
	A quick preview
	Drinking from the firehose
	Training day
	Summary
Chapter 6: Finding Meaning
	Additional setup
	Skills learned
	Summary
Chapter 7: Making Money with Machine Learning
	Inputs and approaches
		Getting the data
	Approaching the problem
		Downloading and modifying data
		Viewing the data
		Extracting features
		Preparing for training and testing
		Building the network
		Training
		Testing
	Taking it further
	Practical considerations for the individual
	Skills learned
	Summary
Chapter 8: The Doctor Will See You Now
	The challenge
	The data
	The pipeline
		Understanding the pipeline
		Preparing the dataset
		Explaining the data preparation
		Training routine
		Validation routine
		Visualize outputs with TensorBoard
			Inception network
	Going further
		Other medical data challenges
		The ISBI grand challenge
		Reading medical data
	Skills Learned
	Summary
Chapter 9: Cruise Control - Automation
	An overview of the system
	Setting up the project
	Loading a pre-trained model to speed up the training
		Testing the pre-trained model
	Training the model for our dataset
		Introduction to the Oxford-IIIT Pet dataset
			Dataset Statistics
			Downloading the dataset
			Preparing the data
		Setting up input pipelines for training and testing
		Defining the model
		Defining training operations
		Performing the training process
		Exporting the model for production
	Serving the model in production
		Setting up TensorFlow Serving
		Running and testing the model
		Designing the web server
			Testing the system
	Automatic fine-tune in production
		Loading the user-labeled data
		Performing a fine-tune on the model
		Setting up cronjob to run every day
	Summary
Chapter 10: Go Live and Go Big
	Quick look at Amazon Web Services
		P2 instances
		G2 instances
		F1 instances
		Pricing
	Overview of the application
		Datasets
		Preparing the dataset and input pipeline
			Pre-processing the video for training
			Input pipeline with RandomShuffleQueue
		Neural network architecture
		Training routine with single GPU
		Training routine with multiple GPU
	Overview of Mechanical Turk
	Summary
Chapter 11: Going Further - 21 Problems
	Dataset and challenges
		Problem 1 - ImageNet dataset
		Problem 2 - COCO dataset
		Problem 3 - Open Images dataset
		Problem 4 - YouTube-8M dataset
		Problem 5 - AudioSet dataset
		Problem 6 - LSUN challenge
		Problem 7 - MegaFace dataset
		Problem 8 - Data Science Bowl 2017 challenge
		Problem 9 - StarCraft Game dataset
	TensorFlow-based Projects
		Problem 10 - Human Pose Estimation
		Problem 11 - Object Detection - YOLO
		Problem 12 - Object Detection - Faster RCNN
		Problem 13 - Person Detection - tensorbox
		Problem 14 - Magenta
		Problem 15 - Wavenet
		Problem 16 - Deep Speech
	Interesting Projects
		Problem 17 - Interactive Deep Colorization - iDeepColor
		Problem 18 - Tiny face detector
		Problem 19 - People search
		Problem 20 - Face Recognition - MobileID
		Problem 21 - Question answering - DrQA
	Caffe to TensorFlow
	TensorFlow-Slim
	Summary
Chapter 12: Advanced Installation
	Installation
		Installing Nvidia driver
		Installing the CUDA toolkit
		Installing cuDNN
		Installing TensorFlow
		Verifying TensorFlow with GPU support
	Using TensorFlow with Anaconda
	Summary
Index