Neetish Kumar

my-api

February 12, 2024 – February 12, 2024

my-api — GitHub repository

infineontest

February 12, 2024 – February 12, 2024

infineontest — GitHub repository

Assignment_Beer_rating_Algoscale

October 25, 2020 – October 25, 2020

This data set is a Beer data-set & expected to build a Machine Learning model that predicts the overall rating of the beer.

cab-fare-prediction

May 19, 2020 – May 19, 2020

You are a cab rental start-up company. You have successfully run the pilot project and now want to launch your cab service across the country. You have collected the historical data from your pilot project and now have a requirement to apply analytics for fare prediction. You need to design a system that predicts the fare amount for a cab ride in the city.

Prediction-of-liability-of-Personal-loan-prediction

May 19, 2020 – May 19, 2020

This case is about a bank (Thera Bank) whose management wants to explore ways of converting its liability customers to personal loan customers (while retaining them as depositors). A campaign that the bank ran last year for liability customers showed a healthy conversion rate of over 9% success. This has encouraged the retail marketing department to devise campaigns with better target marketing to increase the success ratio with minimal budget.

Real-Estate

May 19, 2020 – May 19, 2020

Prices of real estate properties are sophisticatedly linked with our economy. Despite this, we do not have accurate measures of housing prices based on the vast amount of data available. Therefore, the goal of this project is to use machine learning to predict the selling prices of houses based on many economic factors

Bank-Loan-Defaulter-Prediction

May 19, 2020 – May 19, 2020

Predictive analytics is the stream of advanced analytics which utilizes diverse techniques like mining, predictive modelling, statistics, machine learning and artificial intelligence to analyze current data and predict future. Loans default will cause huge loss for the bank so they pay much attention on this issue to apply various method to detect and predict default behaviors of their customers. The loan default dataset has 8 variables and 850 records, each record being loan default status for each customer. Each Applicant was rated as “Defaulted” or “Not-Defaulted”. New applicants for loan application can also be evaluated on these 8 predictor variables and classified as a default or non-default based on predictor variables.

Santander-Customer-Transaction-Prediction

May 17, 2020 – May 19, 2020

In this challenge, we need to identify which customers will make a specific transaction in the future, irrespective of the amount of money transacted.

Bike-Rental-Analysis

May 17, 2020 – May 19, 2020

Choosing bike sharing system as a medium of transport will allow an eco-friendlier way of transportation. A bike rental is a bicycle business that rents bikes for short periods of time. Bike rental shops rent by the day or week as well as by the hour, and these provide an excellent opportunity for people like travelers and tourists, who don't have access to a vehicle. Specialized bike rental shops thus typically operate at beaches, parks, or other locations that tourists frequently visit. In this case, the fees are set to encourage renting the bikes for a few hours at a time, rarely more than a day. The objective of this Case is to predict the bike rental count based on the environmental and seasonal settings, so that required bikes would be arranged and managed by the shops according to environmental and seasonal conditions.