Aswath98

COVID19

COVID Data Dashboard with Power BI

DecisionTree

Implementation of Decision Tree without inbuilt function in R

demand_forecasting

Janatahack

deploy

Deployment of my first ML project

firestations

Hackerrank

hackethon

instagram-locations

Scraping All Instagram Locations with Python

Intern

Hackethon

MarketingAnalytics

This project is a hackathon conducted by Analytics Vidhya, is a market business problem where sales of each store must be predicted.

Aswath98/MarketingAnalytics

This project is a hackathon conducted by Analytics Vidhya, is a market business problem where sales of each store must be predicted.

Aswath98/COVID19

COVID Data Dashboard with Power BI

Aswath98/DecisionTree

Implementation of Decision Tree without inbuilt function in R

Aswath98/demand_forecasting

Janatahack

Aswath98/deploy

Deployment of my first ML project

Aswath98/firestations

Aswath98/Hackerrank

Aswath98/hackethon

Aswath98/instagram-locations

Scraping All Instagram Locations with Python

Aswath98/Intern

Hackethon

Aswath98/Janatahack

JanataHack - E-Commerce Analytics ML Hackathon

Aswath98/Janatahack-Banking

Have you ever wondered how lenders use various factors such as credit score, annual income, the loan amount approved, tenure, debt-to-income ratio etc. and select your interest rates? The process, defined as ‘risk-based pricing’, uses a sophisticated algorithm that leverages different determining factors of a loan applicant. Selection of significant factors will help develop a prediction algorithm which can estimate loan interest rates based on clients’ information. On one hand, knowing the factors will help consumers and borrowers to increase their credit worthiness and place themselves in a better position to negotiate for getting a lower interest rate. On the other hand, this will help lending companies to get an immediate fixed interest rate estimation based on clients information. Here, your goal is to use a training dataset to predict the loan rate category (1 / 2 / 3) that will be assigned to each loan in our test set. You can use any combination of the features in the dataset to make your loan rate category predictions. Some features will be easier to use than others.

Aswath98/kaggle

Aswath98/Mobility-Analysis

Analytics Vidhya Hackethon

Aswath98/samhar

Hackethon

Aswath98/Web-Analytics

Ninth Semester

Aswath98/WomensHackethon

It is a nation womens hackethon conducted by Analytics Vidhya