Overview
Introduction
Feature engineering
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Feature Handling (8:48)
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Handling Missing Data - Part 1 (6:45)
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Handling Missing Data - Part 2 (7:06)
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Handling Missing Data Notes
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Handling Outliers - Part 1 (6:25)
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Handling Outliers - Part 2 (7:57)
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Handling Outliers Notes
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Binning (9:30)
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Binning Notes
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Encoding - Part 1 (7:24)
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Encoding - Part 2 (8:04)
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Encoding Notes
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Scalling - Part 1 (9:42)
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Scalling - Part 2 (8:34)
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Scalling Notes
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Downloadable IPYNB File Notes
Machine Learning Terminologies
Linear Regression - Regression Analysis
Linear regression - Univariate Regression
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Univariate Regression Theory - Part 1 (7:32)
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Univariate Regression Theory - Part 2 (5:06)
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Univariate Regression Theory - Part 3 (6:03)
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Univariate Regression Theory - Part 4 (7:22)
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Univariate Regression Theory - Part 5 (7:02)
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Univariate Regression using sklearn Theory (4:10)
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Univariate Regression Lab - Part 1 (8:08)
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Univariate Regression Lab - Part 2 (8:29)
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Univariate Regression Lab - Part 3 (6:50)
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Univariate regression - Evaluation metrics of Regression Lab (13:23)
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Univariate Linear Regression Notes
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Downloadable IPYNB File Notes
Linear Regression - Multivariate Regression
Linear Regression - Polynomial Regression
Linear Regression - Decision Tree Regression
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Decision Tree Introduction Theory (8:59)
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Decision Tree Regression Theory (8:55)
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Random Forest Regression Theory (7:26)
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Decision Tree Regression Lab (8:48)
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Visualize decision tree Regressor Lab (9:21)
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Random forest Regressor Lab (6:28)
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Decision Tree and Random Forest Regression Notes
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Downloadable IPYNB File Notes
Linear regression - Hyperparameter Tuning
Regression Project
Model Diagnotics
Classification
Logistic Regression
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Logistic Regression Intro (6:32)
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Logistic Regression Maths intuitions Theory - Part 1 (5:26)
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Logistic Regression Maths intuitions Theory - Part 2 (9:17)
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Logistic Regression Maths intuitions Theory - Part 3 (7:29)
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Logistic Regression Lab - Part 1 (5:07)
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Logistic Regression Lab - Part 2 (8:22)
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Logistic Regression Lab - Part 3 (10:19)
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Logistic Regression Lab - Part 4 (8:07)
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Logistic Regression Lab - Part 5 (6:10)
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Logistic Regression (optional) (6:09)
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Logistic Regression Notes
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Downloadable IPYNB File Notes
KNN
SVM
Decision Tree
Random Forest
Classification Project
K-means Clustering
PCA
