## Learning Plan - Zero to Machine Learning Pro in Hours (Not Years) - Join DS4B 101-R to Unlock

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# Learning Plan - Zero to Machine Learning Pro in Hours (Not Years)

**Before we get started - ****The information you are about to learn literally took me years to compile and understand. You will learn modeling in hours - This is no small feat, but - with my streamlined approach - you will become very good very fast.**

## Here is what the Learning Plan entails.

Machine Learning is a difficult concept, but a necessary one that will open you to a **new world of possibilities** in data analysis. To get up to speed quickly, you will need to learn **theory, terminology, core algorithms, and application**. This is no small feat. The good news is I've designed a learning path to get you up to speed in hours (not days, months, or years). Here's how we are going to do it.

**Machine Learning Regression Cheat Sheet**- This resource is covers every major topic related to using machine learning for regression in 2 pages.**Machine Learning Theory**- StatQuest has excellent videos on Machine Learning Theory. Viewing these videos will expose you to the theory and concepts behind machine learning first, before we dive in.**Summary & Terminology**: We have a 10 minute video that covers the Summary & Terminology Sections of theon Page 1. This will introduce you to the terminology.*Machine Learning Regression Cheat Sheet***Modeling Algorithms Overview:**We have a 10 minute video that covers the Machine Learning Algorithm Attributes Table of theon Page 2. This will introduce you to the core algorithms.*Machine Learning Regression Cheat Sheet*

Then we jump into the individual algorithms with theory and application.

*The following section will take about 3-5 hours to complete. When finished, you will be proficient at modeling & machine learning. Complete everything - this will accelerate your learning.*

**Algorithm Theory & Application**

I've combined (1) Page 2 of the __ Machine Learning Regression Cheat Sheet__, (2) StatQuest videos on individual algorithms, and (3) lectures showing you how to APPLY the algorithms.

**This forms a 3-headed monster of learning - you get the 1000-foot view overview + model theory + model application.**Here's the roadmap:

**Linear Models**- Linear Regression

- Generalized Linear Models (GLM) - Elastic Net

**Tree-Based Models**- Decision Trees
- Random Forest
- XGBoost (Gradient Boosted Machine, GBM)

**BONUS - Support Vector Machine & Preprocessing**

With this roadmap, you will be able to learn the basics of modeling using all of the core algorithms that I use every day. Further, you will understand how they work along with their strengths and weaknesses. **This information literally took me years to learn. You will learn modeling in hours.**

Have fun, get excited, you are doing great.

-Matt

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