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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“Xamarin University Presents” Webinar series
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