Analytics

Not a course in Machine Learning


John Alexis Guerra Gómez| ja.guerrag[at]uniandes.edu.co| @duto_guerra
Jose Tiberio Hernández | jhernand[at]uniandes.edu.co
Universidad de los Andes


http://johnguerra.co/lectures/visualAnalytics_fall2019/14_Analytics/

Outline

  • Clustering
  • Regression
  • Classification
  • Dimensionality Reduction
  • Recommendation systems

Clustering

http://scikit-learn.org/stable/modules/clustering.html#clustering

When to use it?

  • When you want to find similar items
  • Depends on your distance metric
  • When you have to many items, and you want to aggregate

Examples

  • Customer segmentation
  • Grouping experiment outcomes

Regression

http://scikit-learn.org/stable/modules/linear_model.html#passive-aggressive-algorithms

When to use it?

  • Present (Identify/Compare) Tendency
  • Predict values

Linear Regression

http://blockbuilder.org/tmcw/3931800by tmcw

Examples

  • Stock prices
  • Drug response

Classification

Classification algorithmshttps://scikit-learn.org/stable/modules/ensemble.html#random-forests

When to use it?

  • Present (Identify/Compare) Tendency
  • Present (Identify/Compare) Groups
  • Aggregate
  • Predict values

Examples

  • Photo categorization
  • Sentiment analysis
  • Spam filtering

Dimensionality Reduction

When to use it?

  • Attribute Filtering
  • Categorize Documents (Topic modeling)

Recommendation systems

When to use it?

  • Large catalog, with user preference history
  • If you like a, and b, maybe you will like c

Types

  • Collaborative filtering
  • Content based systems
  • Hybrids

Examples

  • Amazon
  • Facebook
  • Google
  • Yahoo
  • Netflix Prize

How to use the algorithms?

Applied example node + R

https://github.com/juanibarral/node_plus_r_tutorial/wiki