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NNFL

[College Project] - BITS F312

Implementation of different machine learning algorithms with the help of matlab, python3 and jupyter notebook. You can also look at implementation of cross validation partition, both using k-fold and holdout splits using iris dataset. Autoencoders are also implemented using the same.

Table of contents


Summary

Did respective college (3)assignments.

Problems Assignment-1
1 Linear Regression
2 Stochastic Gradient Descent
3 Ridge Regression
4 Vectorized Linear Regression
5 Least Angle Regression
6 unsupervised learning
7 Logistic Regression for binary class
8 Logistic Regression for multi class
9 Logistic Regression for multi class
10 Likelihood ratio test
11 Maximum A Posteriori
12 Maximum Likelihood
Problems Assignment-2
1 Multi layer perceptron based Neural Network(2 hidden layers)
2 Radial basis function NN
3 Stacked Autoencoder
4 Extreme learning machine
5 Stacked Autoencoder+ELM
Problems Assignment-3
1 Convolutional Neural Network
2 Conv2D Transpose
3 ANFIS

This was challenging since it was my first time using matlab,and doing data analysis using it.


Technologies

  • Python3.6
  • Matlab

Modules

  • keras
  • sklearn

Matlab_Functions

  • xlsread, ones, size, mean, std, randperm, length, plot, xlabel, ylabel, clear, plot3, contour, scatter, sqrt, sum, find, display, confusionmat, trace, min, cvpartition, norm, kmeans, max, trainAutoencoder, encode, stack, train, stackednet, pinv, tanh, randn, normpdf