ABHINAV GOLI

• Gathered and acquired data from various sources including databases, APIS's and external sources using SQL and Snowflake. Carrying out the preprocessing of structured and unstructured data including Processing, cleaning, and validating the integrity of data to be used for analysis
• Created predictive and descriptive models to solve specific business problems using machine learning Algorithms.
• Provided comprehensive analysis and recommended solutions to address complex business problems and issues using data from internal and external sources and applied advanced analytical methods to assess factors impacting growth and profitability across product and service offerings.

• completed an internship focused on exploratory data analysis and feature engineering.
• Gained in-depth knowledge of SQL by performing complex SQL queries consisting of window functions and joins.
• Attained higher accuracy of 8-15% by refining algorithms through a thorough understanding of various supervised models.

1)Crop Recommendation Yield Prediction System :

• Developed XGBoost and Ridge regression models to suggest crops and forecast yields, that achieved an accuracy of 96.48% and an RMSE value of 0.78
• Deployed models using Flask and Docker , and hosted models on AWS EC2 instance for accessibility and scalability

2)Predict power generated by Windmills :

• Leveraged a comprehensive methodology encompassing data cleansing, feature engineering, exploratory data analysis, and data modeling to accurately forecast power generation. •Employed an XGBoost classification model with parameter estimation using Mean Squared Error (MSE), resulting in exceptional performance.