[College Course] - Course: BITS F312 Neural Network and Fuzzy Logic
[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.
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.