Shobana Arumugamangalam Iyyasami

Data Analyst who plays the data game by strategically moving Python, SQL, and visualization tools to checkmate complex datasets and unveil actionable insights. Crafts narratives from numbers, ensuring every move counts in the quest for data-driven decision-making.

Azure AI Fundamentals

Analysis of Abandoned Animals - Baton Rouge| Python - Pandas, Seaborn, Matplotlib, Flask   May 2024 - June 2024

Scraped 8 years of data of animal control incidents from Baton Rouge Animal Control Rescue Center.

Performed an in-depth exploratory data analysis on 150,000 records and employed analytical methods to identify the animal breeds at high risk of abuse.

Generated visualizations for the results in Python and developed a web page to report this data using Python Flask.

Analysis of Hotel Reviews Using Deep Learning Technique | Python - Scikit-learn, TWINT  Aug 2022 - Dec 2022

Aggregated and prepared a Deceptive Opinion Spam Corpus by mining tweets from Twitter using TWINT OSINT tool and built binary classifiers for sentiment analysis of hotel reviews.

Accomplished state of the art accuracy of 96.09% using a Naive Bayes classifier and an accuracy of 78.97% using the Average Perceptron Model.

Music Analysis: Genre Prediction using Music Information Retrieval | Pandas, Scikit-learn                   Mar 2022 - May 2022

Predicted the genre of music among 12 genres in a Free Music Archive dataset containing 100k plus tracks using quantifiable features of a track like measure of acousticness, energy etc using supervised learning models such as K-Nearest Neighbor, Logistic Regression, Naive Bayesian Classifier, Random Forest and Decision Tree Classifier.

Achieved an accuracy of 86.91% with the Decision Tree Classifier after Feature Selection.