An Introduction to Machine Learning Using TensorFlow

AN INTRODUCTION TO MACHINE LEARNING USING TENSORFLOW
JON STACE
@JONSTACE

What is Machine Learning
A technology that gives computers the ability to
learn using large datasets instead of hard coded
rules

What is it not?
Skynet
https://www.flickr.com/photos/31029865@N06/14997552775

What is it not?
Magic
https://en.m.wikipedia.org/wiki/File:Magic_wand.svg

What is it not?
Big Data
https://commons.wikimedia.org/wiki/File:BigData_2267x1146_white.png

Artificial Intelligence
Intelligence demonstrated by machines
Cognitive Functions
Machine Learning
Deep Learning

Why Bother?
Availability of data
Availability of tools
Don’t need to be a ML researcher/expert

Why not?
You don’t always need it
When you’ve already worked out the classification
You need to understand the options for algorithms

Examples of the use of ML
Titanic passenger list
Netflix
Retail
Importing Data
Insurance Risk Engineering

Basic Approach to Machine Learning

ML Categories
Supervised learning
Unsupervised learning
Reinforcement learning

Algorithms
Regression
Classification
Multi-class and two-class
Clustering
Anomaly Detection

An Introduction to Machine Learning Using TensorFlow

Machine Learning Technologies
TensorFlow
Azure Machine Learning
IBM Watson
R
mlpack
Microsoft Cognitive Toolkit

Why TensorFlow?
Flexible, comprehensive
Free!
High-level and low-level APIs
Works offline
GPU and TPU acceleration
Popular

Installation
Don’t have to stay on Python 2
Python 3.6, not 3.7
pip install tensorflow
Or
pip install tensorflow-gpu

Code Demo
https://github.com/jonstace/tensorflowpresentation

TensorFlow in other languages
C++ core library (C API)
Just the low-level API
Google maintain Python, Java, C and Go support
TensorFlow.js
C#
https://github.com/migueldeicaza/TensorFlowSharp

Summary
Machine Learning – what it is and isn’t
Example usages
Types of ML and the various algorithms
ML Technologies
TensorFlow in Python
TensorFlow in C#

Further Resources
Free Statistics books (https://openstax.org/details/books/introductory-
statistics)
edX course on Machine Learning
(https://courses.edx.org/courses/course-
v1:Microsoft+DAT263x+1T2018a/course/)
Microsoft Azure Essentials: Azure Machine Learning
(https://mva.microsoft.com/ebooks#9780735698178)
TensorFlow web site (https://www.tensorflow.org)

Further Resources
Google's machine learning crash course
(https://developers.google.com/machine-learning/crash-course/)
Quick guide to deep learning (https://medium.freecodecamp.org/want-
to-know-how-deep-learning-works-heres-a-quick-guide-for-everyone-
1aedeca88076)
Microsoft page on algorithm choice (https://docs.microsoft.com/en-
us/azure/machine-learning/studio/algorithm-choice) includes link to
PDF cheat sheet!
HumbleBundle (https://www.humblebundle.com/books/machine-
learning-books) LIMITED TIME AVAILABLE

An Introduction to Machine Learning Using TensorFlow

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