https://github.com/helyousfi/ml_from_scratch

https://github.com/helyousfi/ml_from_scratch

Last synced: 7 months ago
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• Host: GitHub
• URL: https://github.com/helyousfi/ml_from_scratch
• Owner: helyousfi
• Created: 2022-07-26T19:47:48.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2022-08-14T00:33:38.000Z (about 3 years ago)
• Last Synced: 2025-02-26T20:37:17.418Z (7 months ago)
• Language: Python
• Size: 59.6 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md

Awesome Lists containing this project

README

          
Matrix calculus : 

  - https://atmos.washington.edu/~dennis/MatrixCalculus.pdf

  

Cheatsheets:

  - https://www.kaggle.com/getting-started/162119

 

Backpropagation for a linear layer :

  - http://cs231n.stanford.edu/handouts/linear-backprop.pdf

Python :

  - (OOP) https://python-course.eu/oop/class-instance-attributes.php

  - (Python + JSON) https://python-course.eu/applications-python/json-and-python.php

  - Keep track of the median value

# What is implemented so far :

  ## Machine Learning :

  - Linear regression from scratch

  - Neural Network from scratch

    - Dense_layer

    - ConvLayer

    - FlattenLayer

    - PoolingLayer

    - Batch Normalization layer

    - Categorical_crossEntropy

    - Activation functions

    - Backward propagation

    - Gradient descent

    

  ## Computer Vision :

  - Data augmentation for object detection:

    - Horizontal flip

    - Vertical flip

    - Random scale

    - Random Crop

    - Random Rotate

  - Loading dataset from JSON file

  ## Image processing

  - Convolution from scratch

  

  ## Python

  - OOP : Encapsulation, Inheritance, data hiding ...

  - Decorators 

  - Generators

  - Leetode : https://github.com/Garvit244/Leetcode

  

  ## Common questions on Computer Vision & ML

  - https://www.projectpro.io/article/computer-vision-engineer-interview-questions/450

  - https://www.interviewquery.com/p/computer-vision-interview-questions

  - https://www.mlstack.cafe/blog/computer-vision-interview-questions

  - https://github.com/badtyprr/computer-vision-interview  (coding)

  

# TODO :

  - Implement Evaluation Metrics

  - Implement CutMix

  - Implement ML models :

    - MLP

    - Logistic regression

    - Support Vector machines

    - Gradient descent

    - Adam optimizer