machine learning and azure ml studio gabc
TRANSCRIPT
Machine Learning and Azure ML Studio
Yogendra Tamang
Global Azure BootCamp16 April, 2016
Outline• Introduction• Case Scenario• Creating Models• Classification• 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 Models1. Create new Experiment2. Type in automobile to see Automobile Price Dataset
1. Play Around with datasets
3. Pre-process Data
Case Scenario
Data Variables
Getting data• Titatanic Data/Automobile Price Data• Each row for single automobile
Data Visualization
Data Pre-Processing
Data Preprocessing• Converting to Categorical [PassengerId,Survived,Pclass,Sex,Embarked]• Missing Value Scrubber• Renaming• Project Columns• Exclude[PassengerId,Name,Ticket,Cabin]
Random Forest
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
Publishing
Thank you
References• https://azure.microsoft.com/en-us/documentation/articles/machine-
learning-create-experiment/