https://github.com/lokranjanp/ml_math

Implementing all the math in basic ML algorithms by scratch using only Numpy
https://github.com/lokranjanp/ml_math

machine-learning mathematics ml-algorithms

Last synced: 5 days ago
JSON representation

Implementing all the math in basic ML algorithms by scratch using only Numpy

• Host: GitHub
• URL: https://github.com/lokranjanp/ml_math
• Owner: lokranjanp
• Created: 2024-09-09T02:55:51.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-09-17T06:27:43.000Z (4 months ago)
• Last Synced: 2024-11-09T18:29:54.763Z (2 months ago)
• Topics: machine-learning, mathematics, ml-algorithms
• Language: Python
• Homepage:
• Size: 5.86 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Math_in_ML

Goal : To understand the basic math concepts used in basic Machine Learning Algorithms.

## 1. Linear Algebra

## 2. Calculus

## 3. Probability

## 4. Statistics

The above concepts will be implemented in scratch using Numpy only.

Later pre-existing libraries like tf, torch will be used to implement the same.

Notes to answer questions like why, how, usecase, advantages will be added alongside the practical implementation.

Feel free to raise issues if any problems are found on the implementation.