Pinned

1. Analyzing-US-accidents-data-using-PySpark-and-Databricks Analyzing-US-accidents-data-using-PySpark-and-Databricks Public

   I have analysed the accidents dataset related to United States of America. To handle the dataset requirements of million+ records, I decided to analyse the dataset using DataBricks which is a cloud…

   Jupyter Notebook

2. Identifying-risky-bank-loans-using-C5.0-decision-trees Identifying-risky-bank-loans-using-C5.0-decision-trees Public

   Illustration of C5.0 decision trees algorithm which is used to identify risky bank loans. C5.0 is used because of the benefits it provides which is, that it is quite opinionated towards pruning.

   R

3. Identifying-risky-bank-loans-using-Random-Forest Identifying-risky-bank-loans-using-Random-Forest Public

   Illustration of Random Forest model on credits data for identifying risky bank loans. Random forest combines the decision trees and train them on different set of observations. By using this I will…

   R

4. Predictive-Analysis Predictive-Analysis Public

   Performed predictive analysis using linear and logistic regression where I compared which algorithm worked best. Later, I also managed to perform boosting algorithm to improve the efficiency.

   R

5. Real-Estate-price-prediction-using-python Real-Estate-price-prediction-using-python Public

   A real estate company wants to predict the prices for the future based on the data available. This way it will help them adjust their budget, change the way they work so as to earn profit and also …

   Jupyter Notebook

6. SQL-project SQL-project Public

   Performing normalisation and analysing the different datasets to gather insights for decision making

   SQL