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Implementing Logistic-Regression and Neural Network from scratch using Numpy and Autograd.

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Logistic_Regression

In this repository, we implement a few Machine Learning Algorithms for classification from scratch. We perform forward propogation and backpropgation from scrath and also using autograd.

NN from scratch is here.

Binnary Logistic Regression is here.

K-Class Logistic Regression is here.


Requiremnets

This repository was written using python 3.7.6, and should work with Python >= 3.6

Other libraries that were used

   - NumPy
   - SciPy
   - Pandas
   - Seaborn
   - Autograd
   - Tensorflow
   - Matplotlib
   - SciKitLearn

Transfer learning on VGG-16 and implementing VGG-1

We also wrote VGG-1 from scratch using tensorflow.keras. Also, trained a VGG-16 architecture using transfer learning to finetune on our dataset.

This can be found here.

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Implementing Logistic-Regression and Neural Network from scratch using Numpy and Autograd.

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