March 26, 2020

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giangtranml/ml-from-scratch

giangtranml/ml-from-scratch

All the ML algorithms, ML models are coded from scratch by pure Python/Numpy with the Math under the hood. It works well on CPU.

repo name giangtranml/ml-from-scratch
repo link https://github.com/giangtranml/ml-from-scratch
homepage https://giangtranml.github.io
language Jupyter Notebook
size (curr.) 21470 kB
stars (curr.) 120
created 2019-03-01
license

Machine Learning from scratch

About

This ML repository is all about coding Machine Learning algorithms from scratch by Numpy with the math under the hood without Auto-Differentiation frameworks like Tensorflow, Pytorch, etc. Some advanced models in Computer Vision, NLP require Tensorflow to quickly get the idea written in paper.

Repository structure

As a software engineer, I follow the principle of OOP to construct the repository. You can see that NeuralNetwork class will use FCLayer, BatchNormLayer, ActivationLayer class and CNN class will use ConvLayer, PoolingLayer, FCLayer, ActivationLayer,… This helps me easily reuse every piece of code I wrote as well as for readable code.

Table of contents

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