There are 1 repository under predective-modeling topic.
My Solutions to 120 commonly asked data science interview questions.
A ML Model That Predict The Percentage of Winning for Each Blue And Red Team in League of Legends
Using past Sport (Cricket) data to predict next win for Team India, in any format of the cricket.
Predicting whether the customer will subscribe to Term Deposits through Machine Learning Algorithms by R.
This repository contains the Tasks of Data science /Deep Learning/Machine Learning Projects offered by Bharat Intern
Performed Predictive Analysis using supervised ML algorithm "Decision Tree" on the customer data to predict if a particular cosmetic item will be sold or not based upon the factors respectively
Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. Consider only the below columns and prepare a prediction model for predicting Price. Corolla<-Corolla[c("Price","Age_
Predecitve model for Stock Return forecast (future prediction) for FTS100 Tech-Mark Series (top technical firms) in UK listed on London Stock Exchange
Predecitve model for Stock Return forecast (future prediction) for top technical firms in UK listed on London Stock Exchange
This is Final Capstone Project for ALY6040 Data Mining Fall 2021 CPS. Primarily to learn Data Analytics, Data Mining and Python. Residential and commercial properties were assessed in Boston. The Boston Globe reported in May 2021 that the competitive Boston housing market drives up costs. As the pandemic continues, people demand larger homes. Finding a home became more difficult as most property managers and realtors could not display their properties to several people. This post was written to help individuals, realtors, and real estate brokers find a property at a reasonable price. We selected to use a few basic machine learning concepts to help us determine the best selling price for the house based on the amount of rooms, location, design, and other characteristics about the bath and kitchen. We only focused on residential property because it was in demand. This study's goal was to improve on initial EDA work by constructing predictive models that solved our business concerns. Finally, optimizing the model's performance.
Classification-Model-to-Identify-Multiple-Disease
hr attrition using supervised learning
Solving Black Friday problem with ml in R
We are analyzing how different factors affect students' overall academic performance as measured by the performance index. Correlation Analysis, Predictive Modeling, Statistical Analysis and Visualization.
Stockwise is a cutting-edge web application designed for efficient inventory management through advanced demand forecasting techniques. This project addresses the critical challenges organizations face in predicting demand, managing stock levels, and ensuring customer satisfaction.
Linear regression and prediction for website