Class Overview

Below are materials for my ongoing Machine Learning for Beginners course. This class covers foundational topics in machine learning including:

• Pre-processing data for modeling
• Model validation
• Machine learning algorithms
• Model evaluation metrics

For ongoing class schedule please join my Data Science & Big Data Meetup

Class Github

Code associated with each course can be found on Github here: https://github.com/kelsey-huntzberry/DataAnalysisLab. Data can be found here.

Python Environments

Class Video and Materials

Machine Learning Basics and Data Pre-Processing

Class Video and Materials

K-Nearest Neighbors and Model Evaluation

Class Video and Materials

Lasso and Ridge Regression

Class Video and Materials

Tree-Based Models, Part 1

Class Video and Materials

Tree-Based Models, Part 2

Class Video and Materials

Feature Importance & Selection

Class Video and Materials

Segmentation

Class Video and Materials

Time Series: Traditional Models

Class Video and Materials

Time Series with Trends & Seasonality

Class Video and Materials

Data Science Tips & Tricks

Class Video and Materials

Becoming a Data Scientist

Class Video and Materials