Xamarin University Instructor

@jdeboever

github.com/jasallen

[DEMO]

[DEMO]

Have questions?

Intro to Machine Learning

DemoMicrosoft Cognitive Services

Data Guess algorithm

Try again

Check

accuracy

HARD!

Clusters

(Color, space)

Scaling value

(Money)

Categories

(Spam, not Spam)

DemoScaling values

(Feature * parameter) + (Feature2 * parameter2)… = guess

Square Feet Bedrooms Price

1000 1 $50,000.00

2000 2 $100,000.00

2000 3 $120,000.00

3000 3 $150,000.00

50% increase

increases price

by 20%

Price increases

linearly with

square feet

Square Feet Bedrooms

1000 1

2000 2

2000 3

3000 3

+ = hWell known

algorithm

Weights /

parameters

Hypothesis /

candidate model

h(x1) = y1

Hypothesis Single

record

Prediction

var guessedHousePrice = LinearRegression(weights, HouseData[0]);

Hypothesis X1

Y1

Square Feet Bedrooms Price

1000 1 $50,000.00

1000 * 50 + 1 * 2000 = 52000

Sq ft * Weight 1 Beds * Weight 2

If we don’t apply feature scaling as

a separate step, we have to make

up for it in the weights

Not quite right, but in the ballpark

Weight Feature 1 Weight Feature 2

50 20000

3

Train algorithm

to determine

optimal weights

1

Start with

historic data

2

Take guess

at algorithm

and weights

+

1. Split data

2. Data cleansing and feature selection

3. Select algorithm and initial weights

4. Train the model

5. Evaluate the model

6. Try other options

DemoAzure Machine Learning Studio

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Explore Azure Machine Learning Studio

studio.azureml.net

Azure Machine Learning introductory content

aka.ms/v95ne3

azure.microsoft.com/en-us/resources/videos/azure-machine-learning-for-software-engineers/

Azure Machine Learning tutorials and samples

gallery.cortanaintelligence.com/experiments

coursera.org/browse/data-science/machine-learning

https://mva.microsoft.com/en-US/training-courses/data-science-and-machine-learning-essentials-14100

Xamarin University self-guided learning and free trial

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