Kunal Devkate

Developed an advanced machine learning model using XGBoost to predict drug effectiveness, leveraging patient reviews and additional feature sets. Implemented TF-IDF vectorization for sophisticated text preprocessing and engineered supplementary features to optimize model performance, resulting in robust and accurate classification outcomes.

Employed time series prediction by ARIMA predictive modeling techniques to forecast quantity and regression price for the upcoming year. Analyzed 3-years historical data for a specific commodity, including price and attributes. Developed a robust and efficient Resume parser model using Python, leveraging natural language processing (NLP) techniques. Innovatively designed and implemented a solution for automating the extraction of relevant information from resumes, streamlining the recruitment process and reducing manual effort. Executed spatial queries, efficiently identifying points within polygons and polygon intersections.

Automated Bank's reports using Python and ML, replacing SQL and Excel. Developed large-scale data extraction systems and customer segmentation algorithms for Bank. Elevated the Bank's operational efficiency by revolutionizing reporting processes through Python and ML, supplanting conventional SQL and Excel methods, and integrating advanced time series analysis techniques for insightful trend forecasting, empowering data-driven decision-making with precision and agility. Extracted text from PDFs using Python, AWS, and ML techniques and used Data Science Filtration methods.