sandesh612 Goto Github PK

-comp2200-practicals

entropy-information-gain

Using Entropy to calculate randomness in the data and calculating information gain to find how much information is a column giving

logistic-regression

Creating training models using Logistic Regrerssion, K Nearest Neighbours (KNN), Decision Tree and Random Forest then doing cross validation for each of them to find best hyper parameters for them after doing so using feature selection method to select best features and finally using best features and hyper parameter to increase the accuracy of the model.

sandesh612

Config files for my GitHub profile.

ss

student-attendance-system-using-face-recognition

Final Year Project

task-manager

To-do list app built using node.js

tax-calculator

Created using HTML, CSS, JS, PHP, MySQL

vegetable-classification-using-cnn

Created cnn model using rescaling layer , 3 convolution layer with relu activation each of them having max pooling layer. Used adam optimizer and sparse categorical crossentropy for loss function. Did data augmentation as the giving data was less for training and testing the model.

weather-website

Shows weather for each location