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forecasting-the-sales-of-a-furniture-store

One of the most important tasks for any retail store company is to analyze the performance of its stores. The main challenge faced by any retail store is predicting in advance the sales and inventory required at each store to avoid overstocking and under-stocking. This helps the business to provide the best customer experience and avoid getting into losses, thus ensuring the store is sustainable for operation. Problem Statement: Read the superstore data and forecast about the sales of furniture for the next year.

house-price-prediction

EDA and Linear Regression on the house price dataset and Analysis to predict the house price.

human-activity-recognition

This Project is based on the human activity detection. In this project we have collected the data of 12 activities from the sensors of the smartphone using Andro-Sensor mobile application then we have perform EDA and performed required statistical calculation and added it in our training dataset in feature engineering. We have visualise the high demensional data using t-SNE and implemented machine learning classifier SVM using poly and rbf kernel, KNN, Logistic Regression, Decision Tree , XGBoost then applied GridSearch to get best parameters and we got best accuracy in Logistic Regression and we have successfully tested new test data in model. This model can be used for health monitoring activities pattern.

incubyte-assessment

predicting-term-deposit-subscription-by-a-client

Marketing campaigns are characterized by focusing on the customer needs and their overall satisfaction. Nevertheless, there are different variables that determine whether a marketing campaign will be successful or not. There are certain variables that we need to take into consideration when making a marketing campaign. A Term deposit is a deposit that a bank or a financial institution offers with a fixed rate (often better than just opening a deposit account) in which your money will be returned back at a specific maturity time. Problem Statement: Predict if a customer subscribes to a term deposits or not, when contacted by a marketing agent, by understanding the different features and performing predictive analytics

prediction-of-runs-in-an-inning

This project is based on the official dataset of IPL and contains detailed information of each inning from 2008 to 2020. In this project we have work on multiple datasets and did data cleaning and feature engineering to get required feature in our final training dataset. Then using pipeline we have perform Linear Regression, Decision Tree, RF regressor, SVM then GridSearch to get best parameters and based on this RF regressor was our best model and performed Cross-validation then We have tested this model for prediction of single match and successfully visualize the actual and predicted runs scored by batsman in an inning. This model is useful for many sport analyst as well as team building.