Handbook of Hidden Data Scientist (R)
  • Introduction
  • References
  • Install R
    • Mac OSX
    • Windows
    • Linux
  • Basics
    • Analysis Types
    • Machine Learning
    • Tidy data set
  • R
    • Limitations
    • Documentation
    • Coding Standards
    • Basics and Data Types
    • Data Table
    • Textual Serialization
    • Control Structures
    • Functions
    • Packages
    • Vectorized Operations
    • Date and Time
    • Loop Functions
    • Split Function
    • Random Variables
    • Simulate Linear Model
    • Debugging
    • Profiler
  • Reading and Writing
    • Files
    • Larger Datasets
    • CSV
    • Excel
    • JSON
    • XML and Web pages
    • REST API
    • MySql
    • HDF5
    • Other...
  • Cleaning Data
    • Subsetting
    • Summarizing
    • New Variables
    • Reshaping
    • Merging
    • Editing text
    • Regular Expressions
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  • Supervised learning
  • Unsupervised learning

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  1. Basics

Machine Learning

Supervised learning

Somebody tells you how things look like. For example, this is how a house looks like. Then you can decide whether the other objects are houses or not.

Unsupervised learning

You figure out what things look like based on similarity and features.

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Last updated 5 years ago

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