MACHINE_LEARNING.md

Machine Learning

Machine Learning is the study of computer algorithms that improve automatically through experience.

Basic Crash Course

For starting ML from right from basics, setting everything up and getting an idea about various things, you can follow this crash course video by Academind.

Complete Courses

• For learning deep, advanced concepts of ML and become an expert, you can go ahead with this paid course on Udemy.

• Build Machine Learning Projects

• Machine Learning for Absolute Beginners

Diving Deep

Topics to Cover

* Pandas and Numpy for Data Pre-Processing and Analysis.
* Matplotlib and Seaborn for Data Visualization.
* Sklearn to implement Machine Learning Models.
* Error Measurement and Scaling techniques.
* All methods and techniques mentioned are listed below:

Data Preprocessing and Visualization

1. Pandas 🐼
   • Pandas Tutorial
   • Check out this Awesome Repo
2. Numpy
   • Numpy Tutorial
3. Matplotlib
   • Matplotlib Tutorial
4. Seaborn
   • Seaborn Tutorial

Machine Learning ⚡

1. Models

   • LinearRegression

     • Linear Regression
     • Multi Variable LinearRegression Video
     • MultiVariable Explanation

   • LogisticRegression

     • Explanation
     • Explanation with Example
     • Video Explanation

   • Naive Bayes

     • Explaination
     • Video Explaination

   • DecisionTreeRegressor

     • Decision Trees
     • Video Explanation

   • RandomForestRegressor

     • Article Explanation
     • Video Explanation

   • KNeighborsClassifier

     • Code Explanation
     • Kneighbors Explained
     • Video Explanation

   • SVM

     • An Idiots Guide to SVM
     • Video example
     • Another Video

   • IsolationForest

     • Explanation
     • Another Article
     • Isolation Forest Video

   • LocalOutlierFactor

     • Article
     • Video Series

   • AdaBoost

     • Article
     • Video example

   • XGBoost

     • Article
     • Video example

2. Prediction Measurements

• mean_absolute_error
  • Mean Absolute Error
• accuracy_score
  • Accuracy Score
• classification_report
  • Classification Report

3. Scaling

• StandardScaler
  • Standard Scaler
• RobustScaler
  • Robust Scaler
• Difference In Types of Scalers

4. Encoding Categorical Data

• Differenent types of Encoding Techniques
  • Explanation

Beginner Friendly Datasets 🤩

While learning, it is always recommended to implement your knowledge practically. So, these are some project ideas to help you through this process.

S.No.	Title
1.	Titanic Dataset
2.	Brooklyn Home Sales
3.	IBM HR Analytics
4.	Life Expectancy (WHO)
5.	New York City Airbnb