Stock Price Prediction

In this project, I implemented a stock price prediction model using TensorFlow, numpy, pandas, and matplotlib. By leveraging these tools, I successfully developed a model that accurately predicted stock prices, that could enable informed investment decisions.

Data Analysis of 'Mall Sales Data' and Market Segmentation

In a previous project, I conducted data analysis on 'Mall Sales Data' and performed market segmentation using sklearn, k-means clustering, and matplotlib. By utilizing these tools, I successfully analyzed the data and identified distinct customer segments, visualizing the results through insightful

Neural Network for Identifying Hand Written Digits

In this project, I employed a neural network along with TensorFlow, numpy, pandas, and matplotlib to develop a model that successfully recognized handwritten digits. Through training and evaluation, the neural network demonstrated accurate and reliable recognition capabilities.

Sales data analysis with SQL and PowerBI

Sales Analytics PowerBI report providing a concise visual summary of revenue trends across various product marketplaces. It highlights insights, such as product performance, market penetration, and revenue growth, empowering data-driven decisions for maximizing sales potential and market strategies.

HR Analytics using SQL and PowerBI

The user-friendly Power BI dashboard provides a detailed Termination Analysis based on gender, age, race, and years of service across different departments, enabling HR professionals to make informed decisions and foster a diverse and inclusive workplace culture.

Customer-Churn and Survival analysis using Machine Learning

This project focused on analyzing customer churn in a telecom company through an extensive descriptive analysis. Various factors influencing churn were explored, followed by predictive analytics using machine learning algorithms like Logistic Regression. The model achieved a significant AUCROC score

Curation of Database for G-Quadruplex Forming Long Non-Coding RNAs

This project focuses on investigating the role of G-Quadruplex-forming long non-coding RNAs (lncRNAs) in cancer regulation. By identifying interactions between G-Quadruplex-forming lncRNAs and protein partners, the project aims to enhance a cancer-related database. This database will encompass dysre

3D Geospatial Population Plots

Utilizing kontur.io data, Rayshader and RayRender in R were seamlessly integrated to produce dynamic 3D population density plots, offering efficient visualization and analysis of spatial patterns.

Credit Risk Analysis and Modelling

Predicting the risk of client default using XGBoost, LightGBM and CatBoost Credit risk is associated with the possibility of a client failing to meet contractual obligations, such as mortgages, credit card debts, and other types of loans.

Delhi Metro Network Analysis

This project aims to deeply analyze the Delhi Metro network, focusing on its stations within the bustling cityscape. By thoroughly cleaning data, using visualization tools, and conducting detailed analysis, we seek to uncover insights about station evolution, distribution, ridership, and network.