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 the Machine Learning Regression Cheat Sheet on Page 1. This will introduce you to the terminology.
- Modeling Algorithms Overview: We have a 10 minute video that covers the Machine Learning Algorithm Attributes Table of the Machine Learning Regression Cheat Sheet on Page 2. This will introduce you to the core algorithms.
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.