WebTrafficForecasting

Web traffic over pages have been foretasted using "TIME SERIES- ARIMA, BOOSTING METHODS OF REGRESSION and PROPHET".

LoanPrediction-KernelSVM-RandomForest-NeuralNetwork-XGBoost

Four models (SVM Kernel, XG Boost, Random-Forest and Neural Network) were applied over a data which supplies us information about the customers & asks to predict whether loan should be given to them or not. Used K-Fold Cross Validation to avoid over-fitting and used Grid Search for tuning parameters.

Sentimental-Analysis-on-Youtube-Data

Sentimental Analysis performed on the comments of youtube videos and each youtube video is given a rating based on number of positive and negative sentiments. Also performed Exploratory Data Analysis for the videos.

RecommendationSystem-RBM-PyTorch

From the previous ratings given by user, the script recommends diffrent movies to the user. The system uses Restricted Boltzmann Machine (RBM) for its computations, and this RBM is made from scratch using PyTorch