Machine Learning and Azure ML Studio

Yogendra Tamang

ASPNET Meetup

20 February 2016

Outline

• Introduction

• Creating Models

• Regression

• Creating Models on Azure ML

• Demo

Machine Learning ?

• AI

• Learning Algorithm

• Lots of examples

• Testing and Evaluation

Machine Learning

• Machine Learning- Grew out of work in AI- New capability for computers

• Examples: - Database mining

• Large datasets from growth of automation/web. • E.g., Web click data, medical records, biology, engineering

- Applications can’t program by hand.• E.g., Autonomous helicopter, handwriting recognition, most of Natural Language

Processing (NLP), Computer Vision. - Self-customizing programs

• E.g., Amazon, Netflix product recommendations- Understanding human learning (brain, real AI).

Machine Learning

• Autonomous Helicopter

• Autonomous Driving

• Face Detection

Autonomous Cars, Facial Detection, NLP..

Azure ML

• Create Model• Get Data

• Pre-processing of data

• Define Features

• Train the Model• Choose and apply learning algorith

• Score and Test the model• Predict new automobile prices

Creating Models

1. Create new Experiment

2. Type in automobile to see Automobile Price Dataset1. Play Around with datasets

3. Pre-process Data

Getting data

• Automobile Price Data

• Each row for single automobile

Preprocessing Data

• Clean Missing Values• Normalized-Losses column Remove

• Remove any rows having missing data• Exclude normalized-loss[Use Project Columns]

• Clean rows having missing data [ Clean Missing Data Module]

Defining Features

• Requires experimentation and knowledge about context

• Some feature better at predicting target.

• Strong correlation with other features

Apply Learning Algorithm

• Classification or Regression ???

• Split Data to train and test

• Train [0.75] and test[0.25] … Use split data, Run Experiment

• Machine Learning -> Initialize Model -> Regression->Linear Regression

• Train Model Module

Training the model

• Train Model Module

• Left Port for Model, Right port for data

• Run experiment

Predict New Automobile Prices

• Score Model• Left Port from Train model

• Right Port from Test Data

• Run

• Evaluate Model

Thank you

References

• https://azure.microsoft.com/en-us/documentation/articles/machine-learning-create-experiment/