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Lean ML: The Beginner's Guide to Machine Learning with Python

The Essential Basics

Introduction (0:48)
What is Machine Learning? (7:36)
The ML Ecosystem (3:04)
X & y Variables (1:49)
Model Overview (0:57)
Feature Selection (3:57)
Data Scrubbing (3:30)
Training & Test Data (1:39)
Self-learning Algorithms (13:07)
Classification & Regression (2:50)

Python

Machine Learning Libraries (5:03)

Learning Algorithms

Evaluation (4:37)
Linear Regression (7:30)
Logistic Regression (2:41)
Support Vector Machines (4:07)
Bias & Variance (3:37)
k-Means Clustering (3:02)
k-Nearest Neighbors (2:15)
Decision Trees (2:24)
Random Forests (2:12)
Gradient Boosting (3:56)

Development Environment

Working in Jupyter Notebook (2:55)

Machine Learning in Python

Introducing the Class Project (2:04)
Downloading the Dataset (1:01)
Python Exercise (6:25)

Further Resources

Books, Video Courses & Other Materials (2:17)

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Gradient Boosting

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