• Developed new algorithms, tested and improved existing algorithms that forecast electric load in smart grid, such as Neural Networks, Generalized Linear Models, and time series models.
• Identified inefficiencies in the implementation of machine learning models after ETL and visualizing of raw unstructured data.
• Problem Setter 
• Created quizzes, Minor and Major Projects for students 

• Worked on a project to automatically scrape the specific elements from different course websites.
• Used Supervised Machine Learning models to classify course-related content on the website.
•  Latent Dirichlet Allocation was used for topic modeling to help identify the key drivers of these Sky Clubs (such as Food/Beverages, Friendliness of Staff , Service, etc) that aided in attaining high customer satisfaction ratings.
• Random Forest and XGBoost models were used for detecting overall feature importance to help determine factors that had a significant impact in helping Delta achieve superior NPS scores.

• Analyzed and processed complex data sets using advanced querying, visualization and analytics tools.
• Utilized Web scrapping technique to extract and organize data.
• Prepared reports through data cleaning, data visualization, and writing insights
• Updated data streamlining processes , resulting in 20% redundancy reduction.

• Learnt Python from scratch
• Worked with various Machine Learning algorithms to create the best working models 
• Got familiar with data visualization and performed data analysis on multiple projects 
• The project involved conducting Sentiment Analysis of customer feedback from Delta Sky Club’s across various cities in the USA through the use of Machine Learning techniques. 

• Worked as a python developer.
• Worked on data pre-processing , experience with database systems and AWS services.
• Gained knowledge on the basics of Natural Language Processing.
• Was exploring and figuring out solutions to analyse 1.5 TB of data.