• Performed analysis on data for determining trends
• Developed aLinear Regressionmodel to predict the price of a house
• Measured the error of the model using accuracy measurement formula

• Analyzed data set using pandas, matplolib, seaborn,​​​​ to determine trends in it
• Developed different machine learning algorithms to predict the suitability of a person for loan or not
• Measured theerrorsin models that have been developed

Performed data analysis over credit card fraud detection data and developed different machine learning algorithms to predict occurrence of frauds

Data analysis using SQL over OYO hotel data set for measuring its performance in different cities

Utilized NLP libraries including NLTK and SpaCy for preprocessing tasks such as tokenization, lemmatization, and stopword removal. Conducted sentiment analysis and topic modeling on large volumes of Reddit data to extract insights. Developed a linear regression model to predict user engagement, achieving an 85% accuracy rate, which enhanced content strategy decisions.

Designed and implemented an automated web scraping solution using Selenium and Beautiful Soup to collect job postings from Indeed.com. Scraped and processed 1,000 job postings daily, enabling the creation of a dynamic job market analysis dashboard. Analyzed scraped data to identify hiring trends and skills in demand, resulting in the development of targeted recruitment strategies that improved candidate match rates by 20%.

Developed a machine learning model using Random Forest and Decision Tree algorithms to classify products based on descriptions. Conducted feature engineering and hyperparameter tuning to optimize model performance. Integrated the model into an interactive Streamlit application, allowing users to input product descriptions and receive instant classification results. Achieved an 88% classification accuracy, significantly improving product categorization efficiency for the client.

Leveraged Microsoft Azure SQL Database to manage and analyze large datasets for an e-commerce platform. Designed and executed complex SQL queries to analyze customer purchase behavior, product performance, and sales trends. Developed and maintained ETL processes to ensure data accuracy and consistency. Created interactive dashboards and reports using Power BI, providing real-time insights into key business metrics. Insights from the analysis contributed to a 15% increase in sales and a 10% improvement in customer retention through targeted marketing strategies.