Module 01: Introduction to Machine Learning Algorithms | |||
Introduction to types of ML algorithm | 00:02:00 | ||
Module 02: Preprocessing | |||
Importing a dataset in python | 00:02:00 | ||
Resolving Missing Values | 00:06:00 | ||
Managing Category Variables | 00:04:00 | ||
Training and Testing Datasets | 00:07:00 | ||
Normalizing Variables | 00:02:00 | ||
Normalizing Variables – Python Code | 00:03:00 | ||
Summary | 00:01:00 | ||
Module 03: Regression | |||
Simple Linear Regression – How it works? | 00:04:00 | ||
Simple Linear Regreesion – Python Implementation | 00:07:00 | ||
Multiple Linear Regression – How it works? | 00:01:00 | ||
Multiple Linear Regression – Python Implementation | 00:09:00 | ||
Decision Trees – How it works? | 00:05:00 | ||
Random Forest – How it works? | 00:03:00 | ||
Decision Trees and Random Forest – Python Implementation | 00:04:00 | ||
Module 04: Classification | |||
kNN – How it works? | 00:02:00 | ||
kNN – Python Implementation | 00:10:00 | ||
Decision Tree Classifier and Random Forest Classifier in Python | 00:10:00 | ||
SVM – How it works? | 00:04:00 | ||
SVM – Python Implementation | 00:06:00 | ||
Resources | |||
Resources – Machine Learning with Python | 00:00:00 | ||
Assignment | |||
Assignment – Machine Learning with Python | 5 days, 14 hours | ||
Order Your Certificate | |||
Order Your Certificate QLS | 00:00:00 |
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