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Data Mining with Python: Implementing Classification and Regression
Introduction to Data Mining
The Course Overview (3:55)
A Brief Introduction to Data Mining (4:37)
Data Mining Basic Concepts and Applications (7:05)
Setting Up the Data Mining Python Packages Environment
Why Python? (3:31)
Basics of Python (5:55)
Installing IPython (2:09)
Installing the Numpy Library (4:32)
Installing the pandas Library (5:32)
Installing Matplotlib (2:42)
Installing scikit-learn (2:37)
Cleaning Data and Preprocessing Techniques
Data Cleaning (5:31)
Data Preprocessing Techniques (5:08)
Linear Regression Model
Linear Regression Basic Model Approach (8:23)
Evaluating Regression Models (5:31)
Basic Regression Model Implementation to Predict House Prices (9:20)
Regression Model Implementation to Predict Television Show Viewers (9:46)
Classification Concepts
Logistic Regression (4:01)
K – Nearest Neighbors Classifier (5:51)
Support Vector Machine (5:41)
Logistic Regression Model Implementation (10:45)
K – Nearest Neighbor Classifier Implementation (10:43)
Data Cleaning
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