Decision Trees and Entropy

Fler avsnitt från "intuitions behind Data Science"

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  Loss Function

  2021-12-13

  6:13

  The intuition behind loss function
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  Central Limit Theorem

  2021-12-04

  5:21

  A quick introduction to central limit theorem and why it helps data analysis
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  Causality and Control

  2021-12-03

  7:02

  Thoughts on causality and the need for a control sample
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  Neural Networks

  2021-12-01

  8:34

  Can we think of neural networks as layers of decisions with regression and classification at each layer?
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  Types of Data Attributes

  2021-11-29

  13:00

  What are the different types of data attributes?
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  Intercept

  2021-11-23

  7:29

  Independence of the dependent variable
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  Bias and Variance

  2021-11-23

  6:20

  Generalizing the estimations of population parameters
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  Linear Regression

  2021-11-19

  7:02

  Guessing the recipe of data!
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  Decision Trees and Entropy

  2021-11-19

  6:29

  How are decision trees trained and what is entropy?
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  Validation

  2021-11-17

  9:04

  What is the intuition behind cross-validation for estimating population parameters?