This project use Causal Graph for breast cancer detection based on Breast Cancer Wisconsin (Diagnostic) Data Set. Causal inference refers to an intellectual discipline that considers the assumptions, study designs, and estimation strategies that allow researchers to draw causal conclusions based on data.

In this project, time series analysis is performed to check for trends and seasonality in sales over time for all the Rossmann pharmaceutical sales. An LSTM model, is used to forecast sales in all their stores across several cities six weeks ahead of time

In this project, I analyzed opportunities for growth and make a recommendation on whether a telecom company is worth buying or selling. I did this by analyzing a telecommunication dataset that contains useful information about the customers & their activities on the network. User engagement and experience analysis is mainly done on the project.

In this project, python package is developed to fetch and visualize Lidar data for a given area. The USGS recently released high-resolution elevation data as a lidar point cloud called USGS 3DEP in a public dataset on Amazon. This dataset is essential to build models of water flow and predict plant health and maize harvest.