Hands-On Machine Learning with C# 1st Edition.pdf

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Title Page

Packt Upsell

Why subscribe?

PacktPub.com

Contributors

About the author

About the reviewer

Packt is searching for authors like you

Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Download the color images

Conventions used

Get in touch

Reviews

Machine Learning Basics

Introduction to machine learning

Data mining

Artificial Intelligence

Bio-AI

Deep learning

Probability and statistics

Approaching your machine learning project

Data collection

Data preparation

Model selection and training

Model evaluation

Model tuning

Iris dataset

Types of Machine Learning

Supervised learning

Bias-variance trade-off

Amount of training data

Input space dimensionality

Incorrect output values

Data heterogeneity

Unsupervised learning

Reinforcement learning

Build, buy, or open source

Additional reading

Summary

References

ReflectInsight – Real-Time Monitoring

Router

Log Viewer

Live Viewer

Message navigation

Message properties

Watches

Bookmarks

Call Stack

Searching through your messages

Advanced Search

Time zone formatting

Auto Save/Purge

Example

ReflectInsight Utilities:

Watches

Software Development Kit

Configuration editor

Overview

XML configuration

Dynamic configuration

Main Screen

Summary

Bayes Intuition – Solving the Hit and Run Mystery and Performing Data Analysis

Overviewing Bayes' theorem

Overviewing Naive Bayes and plotting data

Plotting data

Summary

References

Risk versus Reward – Reinforcement Learning

Overviewing reinforcement learning

Types of learning

Q-learning

SARSA

Running our application

Tower of Hanoi

Summary

References

Fuzzy Logic – Navigating the Obstacle Course

Fuzzy logic

Fuzzy AGV

Summary

References

Color Blending – Self-Organizing Maps and Elastic Neural Networks

Under the hood of an SOM

Summary

Facial and Motion Detection – Imaging Filters

Facial detection

Motion detection

Adding detection to your application

Summary

Encyclopedias and Neurons – Traveling Salesman Problem

Traveling salesman problem

Learning rate parameter

Learning radius

Summary

Should I Take the Job – Decision Trees in Action

Decision tree

Decision node

Decision variable

Decision branch node collection

Should I take the job?

numl

Accord.NET decision trees

Learning code

Confusion matrix

True positives

True negatives

False positives

False negatives

Recall

Precision

Error type visualization

Summary

References

Deep Belief – Deep Networks and Dreaming

Restricted Boltzmann Machines

Layering

What does a computer dream?

Summary

References

Microbenchmarking and Activation Functions

Visual activation function plotting

Plotting all functions

The main Plot function

Benchmarking

Summary

Intuitive Deep Learning in C# .NET

What is deep learning?

OpenCL

OpenCL hierarchy

Compute kernel

Compute program

Compute sampler

Compute device

Compute resource

Compute object

Compute context

Compute command queue

Compute buffer

Compute event

Compute image

Compute platform

Compute user event

The Kelp.Net Framework

Functions

Function stacks

Function dictionaries

Caffe1

Chainer

Loss

Model saving and loading

Optimizers

Datasets

CIFAR

CIFAR-10

CIFAR-100

MNIST

Tests

Monitoring Kelp.Net

Watches

Messages

Properties

Weaver

Writing tests

Benchmarking functions

Running a Single Benchmark

Summary

References

Quantum Computing – The Future

Superposition

Teleportation

Entanglement

CNOT

Summary

Hands-On Machine Learning with C# Build smart, speedy, and reliable data-intensive applications using machine learning Matt R. Cole BIRMINGHAM - MUMBAI

Hands-On Machine Learning with C# Copyright © 2018 Packt Publishing All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book. Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information. Commissioning Editor: Pravin Dhandre Acquisition Editor: Aman Singh Content Development Editor: Mayur Pawanikar Technical Editor: Suwarna Patil Copy Editor: Vikrant Phadkey Project Coordinator: Nidhi Joshi Proofreader: SAFIS Indexer: Mariammal Chettiyar Graphics: Tania Dutta Production Coordinator: Shantanu Zagade First published: May 2018 Production reference: 1210518 Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK. ISBN 978-1-78899-494-1 www.packtpub.com

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Contributors

About the author Matt R. Cole is a seasoned developer with 30 years' experience in Microsoft Windows, C, C++, C#, and .NET. He previously wrote a speech and audio VOIP system for NASA for use with the Space Shuttle and a space station. He is the owner of Evolved AI Solutions, a premier provider of advanced ML/Bio-AI technologies. He developed the first enterprise-grade microservice framework (written fully in C# and .NET) used by a major hedge fund in NYC and he also developed the first Bio-AI Swarm framework, which fully integrates mirror and canonical neurons.

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