https://github.com/pb319/stat_ml-learning

It will consist of statistical machine learning from Codebasics youtube playlist as part of my skill enhancement.
https://github.com/pb319/stat_ml-learning

Last synced: 2 months ago
JSON representation

It will consist of statistical machine learning from Codebasics youtube playlist as part of my skill enhancement.

• Host: GitHub
• URL: https://github.com/pb319/stat_ml-learning
• Owner: pb319
• Created: 2024-06-16T13:01:50.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-07-14T12:30:19.000Z (6 months ago)
• Last Synced: 2024-07-15T12:37:57.061Z (6 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 16 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
![Untitled design(1)](https://github.com/pb319/Stat_ML-Learning/assets/66114329/b29add12-9e5a-4142-b88d-2c29fd26842c)

# Stat_ML-Learning

It will consist of statistical machine learning hands-on exercises from Codebasics youtube playlist as part of my skill enhancement.

## Table of Contents

- Exercise 0  : [Self-Written Notes](Statistical.Machine.Learning.pdf)

- Exercise 1  : Simple Linear Regression

- Exercise 2  : Multiple Linear Regression

- Exercise 3  : Graient Descent

- Exercise 4  : Save & Load model

- Exercise 5  : Dummy Variable

- Exercise 6  : train_test_split

- Exercise 8  : LogisticResgression

- Exercise 9  : Decision Tree

- Exercise 10 : Support Vector Machine

- Exercise 11 : Random Forest

- Exercise 12 : K Fold Cross Validation

- Exercise 13 : K Means Clustering

- Exercise 14 : Naive Bayes

- Exercise 15 : Hyperparameter Tuning

- Exercise 16 : Regularization (Ridge, Lasso)

- Exercise 17 : K Nearest Neighbor 

- Exercise 18 : Bagging

- Exercise 19 : Principal Component Analysis

Thank You !! Visit Again 🙏🙏