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Machine Learning Tutorial 22 - Discriminatory Power
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Classroom Contents
Machine Learning
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- 1 Machine Learning Tutorial 1 - Intro to Machine Learning and A.I.
- 2 Machine Learning Tutorial 2 - Intro to Predictive Data Analytics
- 3 Machine Learning Tutorial 3 - Intro to Models
- 4 Machine Learning Tutorial 4 - Generalization (Algorithms)
- 5 Machine Learning Tutorial 5 - Big Data, Data Warehouse, Hadoop, Federation
- 6 Machine Learning Tutorial 6 - Analytical Base Table (ABT)
- 7 Machine Learning Tutorial 7 - Measures of Central Tendency
- 8 Machine Learning Tutorial 8 - Standard Deviation
- 9 Machine Learning Tutorial 9 - Continuous and Categorical Features (Cardinality)
- 10 Machine Learning Tutorial 10 - Binning Data
- 11 Machine Learning Tutorial 11 - Cleaning Bad Data
- 12 Machine Learning Tutorial 12 - Cleaning Missing Values (NULL)
- 13 Machine Learning Tutorial 13 - Imputation
- 14 Machine Learning Tutorial 14 - Cleaning Irregular Cardinality
- 15 Machine Learning Tutorial 15 - Outliers
- 16 Machine Learning Tutorial 16 - Clamp Transformation
- 17 Machine Learning Tutorial 17 - Using Models for New Data
- 18 Machine Learning Tutorial 18 - Algorithms and Models
- 19 Machine Learning Tutorial 19 - Supervised & Unsupervised Algorithms
- 20 Machine Learning Tutorial 20 - Trees and Binary Trees
- 21 Machine Learning Tutorial 21 - Decision Trees
- 22 Machine Learning Tutorial 22 - Discriminatory Power
- 23 Machine Learning Tutorial 23 - Recursion
- 24 Machine Learning Tutorial 24 - Recursion Base Cases
- 25 Machine Learning Tutorial 25 - Intro to the ID3 Algorithm
- 26 Machine Learning Tutorial 26 - ID3 Algorithm Part 2
- 27 Machine Learning Tutorial 27 - ID3 Algorithm Part 3
- 28 Machine Learning Tutorial 28 - Bar Plots (Bar Graphs)
- 29 Machine Learning Tutorial 29 - Histograms
