SANTOSH KUMAR PAUL's Projects
This is a project which predict the price of house with different kinds of features using machine learning regression algorithm.
This is a deep learning model that predict the hand written digits using ANN.
Machine Learning Project which predict the discounts on the products avalaible on Amazon and Flipkart This is the capstone project of Summer Analytics, a primer course on Data Science, conducted by Consulting and Analytics Club of IIT Guwahati. Description Artificial Intelligence is an integral part of all major e-commerce companies today. Today's online retail platforms are heavily powered by algorithms and applications that use AI. Machine learning is used in a variety of ways, from inventory control and quality assurance in the warehouse to product recommendations and sales demographics on the website. Letβs say you want to create a promotional campaign for an e-commerce store and offer discounts to customers in the hopes that this might increase your sales. You have been provided descriptions of products on Amazon and Flipkart, including details like product title, ratings, reviews, and actual prices. In this challenge, you will predict discounted prices of the listed products based on their ratings and actual prices.
This is a project of classification of employee on the basis of their age and salary.
This project predict the authenticity if the news headlines. Based on the previous news headlines the model is trained and test data is provided after the authenticity of the news is predicted.
In this regression task we will predict the percentage of marks that a student is expected to score based upon the number of hours they studied. This is a simple linear regression task as it involves just two variables.
In this ML project we predicted the number of clusters for the iris flower and verified the result using elbow plot and then visually represented it in the scatter plot.
This is a model for the prediction of Carbon dioxide emission by the various kinds of vehicles.
This repository comprised with model of the prediction of per capita income of CANADA using previous records,
It contains the notebook of jupyter notebook which comprised with basic and advanced concepts of python for data science.
Config files for my GitHub profile.
This a project which predicts the stock price of Tesla for a given time period & based upon the previous 10 years of historical data. Here, numerical and sentimental analysis is performed with the help of natural language toolkit (NLKT), Textblob, sklearn etc. By observing the previous trends of the market stock price and sentiments of the news about the market, this model predicted the future variation of the stock market price of TELSA. Basically, four models were trained with the same dataset like: Random Forest, AdaBoost, LGBM & xgboost out of these model LGBM model predicted with the least mean squared error value.
In this project, texts in the images is recognized using logistic regression analysis.