machine learning and azure ml studio
TRANSCRIPT
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).
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
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
Predict New Automobile Prices
• Score Model• Left Port from Train model
• Right Port from Test Data
• Run
• Evaluate Model