Shwedha Srinivasan

Intro

I am a dedicated Masters in Data Science student at the Illinois Institute of Technology with a profound interest in Data Science, Machine Learning, and Data Analysis. My journey includes diverse experiences such as creating a pothole detector and working with big data using tools like HIVE, PIG, and Pyspark.

I am currently learning NLP, LLM, RAG and GIS. My standout proficiency lies in identifying patterns using K-Nearest Neighbors (KNN) and implementing statistical modeling techniques.

Proficient in tools like Python, R, MySQL, Excel, and Tableau, I am well-equipped for comprehensive data analysis, visualization, and modeling, including machine learning classification and regression models. As a well-rounded data scientist, I excel in unraveling intricate relationships within data sets using KNN and statistical modeling techniques. This nuanced approach enhances the precision of my models, emphasizing my commitment to delivering robust and reliable results in data analysis.

During my coursework at IIT, I am also learning how to use mathematics and computer science together and use them to solve complex problems. Please do check out my Projects to know more about the depth of my expertise.

Work

POTHOLE DETECTION

This was my academic project in my Undergraduate, where I and my team built an application to detect potholes present in the roads. This is a live detector wich is fed and annotated over 16,000 images to detect in real time. This works on Yolov4 and feeds on real-time data. This is built on top of Darknet and uses flask for the application

Click the link to view the project.

IPL LIVE SCORE PREDICTOR

This project is based upon a live score predictor of an Indian cricket match (IPL), this works by firstly preprocessing the given data, encoding the data, performing feature selection and engineering and subjecting the essential features under different regressor models. Later the predicted number of runs are displayed as the result of predction.

Click the link to view the project.

PREDICTION OF MAANG STOCKS

This project was done as part of CSP 571 (Data Preparation and Analysis), which aims to detect the stock prices for the next 10 days for M-A-A-N-G companies. Its a prediction based project involoving various analysis techniques.

Click the link to view the project.

PREDICTION OF BITCOIN PRICES USING MACHINE LEARNING

This project was done as a part of CS 584 (Machine learning), it aims to use a comparison based approachto forecast the Bitcoin prices. It uses ARIMA and LSTM in comparison with regression and classification models.

Click the link to view the project.

CREDIT CARD FRAUDULENT ANALYSIS

Analysis of credit card fraudulent details with a globally available dataset. This repository contains code and analysis for credit card fraud detection using various machine learning models. The goal is to build and evaluate different models, compute ROC curves, and display confusion matrices to assess their performance in detecting fraudulent transactions.

Click the link to view the project.

Dashboards

COVID-19 Analysis using Tableau

I have done a Covid-19 Analysis using Tableau, this is a cumulative analysis of Covid based on number of deaths, recoveries and cases.

Click the link to view the project.

Contact

• GitHub
• LinkedIn

Elements

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