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Efficient Machine Learning

Video Introducing this tutorial


Introduction :
Introduction

Preprocessing and Feature Scaling :
Preprocessing Intro
The Dataset
Missing Values
Label Encoder
One-Hot Encoder
Normalization
Standardization

Feature Engineering :
Feature Engineering Intro
Binarization
Principal Component Analysis (PCA)
Installing Featuretools
Manual Feature Engineering
Automatic Feature Engineering
Feature Selection 1 (Intro)
Feature Selection 2 (Univariate Selection)
Feature Selection 3 (Feature Importance)
Feature Selection 4 (Model-Based Feature Selection)
Feature Selection 5 (Recursive Feature Elimination)

Model Evaluation and Selection :
Model Evaluation and Selection Intro
Regression Evaluation
Classification Accuracy
Confusion Matrix - Precision and Recall
F1-score and Fbeta-score
Area Under Curve (AUC)
Evaluation Measures for Multi-Class Classification
Overfitting vs Underfitting
Cross-Validation
Analyzing Learning Curves
Grid Search vs Random Search