Gary Hope

Machine Learning – It’s Not as Hard as You Think

THE WORLD WE LIVE IN Speaker 4 of 17

Followed by

Gillian Staniland

@GaryHope

What is Machine Learning?

Data Science Workflow for Machine Learning

Data and Decisions

Data Science Workflow for Machine Learning

Delivering on one of the old dreams of Microsoft co-founder Bill Gates: Computers that can see, hear and understand. John Platt Distinguished scientist at Microsoft Research

What is Machine Learning?

Predictive computing systems that become smarter with experience

A breakthrough in machine learning would be worth ten Microsofts. Bill Gates

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SQL Server enables

data mining

Computers work on users behalf, filtering

junk email

Microsoft Kinect can

watch users gestures

Microsoft launches

Azure Machine Learning

Microsoft search engine

built with machine learning

Bing Maps ships with ML

traffic-prediction

service

Successful, real-time,

speech-to-speech

translation

Me, Microsoft & Machine Learning 15 years of realizing innovation

John Platt, Distinguished scientist at Microsoft Research

1999 2012 2008 2004 2014 2010 2005

Machine learning is pervasive throughout Microsoft products. “ ”

Why the resurgence in predictive analytics?

When presented with information we tell

ourselves stories, we have biases and we

have a very low level of intuitive

understanding of statistical information

(that’s not to say we cant spend the effort to analyze)

Any sufficiently advanced technology is indistinguishable from magic.. Arthur C. Clarke, 1961 If and to what

extent the magic of Machine Learning changes YOUR world depends on how YOU use it!

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If you not actually using the data available to make

systematic decisions in your business you will mostly be guessing or at best relying

heavily on potentially biased intuition

The United States Postal Service processed over 150 billion pieces of mail in 2013—far too much for efficient human sorting. But as recently as 1997, only 10% of hand-addressed mail was successfully sorted automatically.

The challenge in automation is enabling computers to interpret endless variation in handwriting.

By providing feedback, the Postal Service was able to train computers to accurately read human handwriting.

Today, with the help of machine learning, over 98% of all mail is successfully processed by machines.

How Does Machine Learning Work?

1 1 5 4 3

7 5 3 5 3

5 5 9 0 6

3 5 2 0 0

The ease of implementation makes machine learning accessible to a larger number of investigators with various backgrounds—even non-data scientists.

Bertrand Lasternas Carnegie Mellon

Smart Buildings: IoT and ML example The Center for Building Performance and Diagnostics uses weather forecasts, real-time temperature reads, and behavioral research data to optimize building heating and cooling systems in real-time.

Key Benefits •  User friendly set up and integration with

existing systems •  Seamless data handling •  Accessible and easy to use across

backgrounds •  Quickly compare algorithms

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Imagine what machine learning could do for your business.

Churn analysis

Equipment monitoring

Spam filtering

Ad targeting

Recommendation

Fraud detection

Image detection &

classification

Forecasting

Anomaly detection

Using past data to predict the future

Common Classes of Problems

Classification Regression Recommenders Anomaly Detection

Some quick theory: Linear Models

Machine Learning Problem Requirements

Available data •  Related to the decision •  Historical •  Outcomes

Valuable business problem involving a decision

–  Existing process –  Metrics

Universal Machine Learning Flow •  Define Objective •  Measurable and has supporting data •  Collect & Prepare Data •  Flatten schema, •  normalize and common scale •  Feature selection •  Sample and split •  Train Model •  Algorithm selection •  Parameter Sweeping •  Analyze Results •  Score, evaluate and visualize

Define Objective

Collect & Prepare

Data

Train Model

Analyze Results

Put ML into Production

Technically make available as a published service Share usage and outcome information inside of the organization.

Define

Prepare

Train

Analyze

Publish

Use

Monitor