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: 8 months ago
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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 (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-09-17T06:27:43.000Z (about 1 year ago)
- Last Synced: 2025-01-05T06:41:50.962Z (10 months ago)
- Topics: machine-learning, mathematics, ml-algorithms
- Language: Python
- Homepage:
- Size: 5.86 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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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.