• English Newspaper Headline Classification Mar 21 – May 21Classified the Newspaper Headlines into Politics, Sports, Education, Healthcare, Finance (5- Class Labels) with the help of Sentiment Analysis, employing Scikit-Learn library and NLTK (Natural Language Toolkit).Technologies Used: Python, Jupyter Notebook, Algorithms: Multinomial Naive Bayes Classifier, One-Vs Rest SVM Support Vector Machine•Handwritten Digit Classification Implemented Multi-Layer Artificial Neural Networks (ANN) on MNIST handwritten digit database that recognized the input handwritten digit with the help of sigmoid function.Technologies Used: Python, Jupyter Notebook, Algorithms: Artificial Neural Networks (ANN)•Recipe Management REST based API Implemented REST based API for Recipe Management Application has functionality to perform operations such as add, modify, delete the recipes, along with retrieval operations. Technologies Used: Python, Flask, docker

• Developed a House Price Prediction model using Xgboost regressor and Linear Regression which helped clients to buy a house at a low price and invest in the features that give the highest return.• Built a Predictive model for examining the employee’s yearly performance using a Logistic • Data Analysis and Feature selection on Insurance Claim data regression algorithm• Worked on LSTM spare parts forecasting predictive model• Data Analysis on Cove19 spread prediction