Graduate student in physics at UCLA. ©

Achievement-driven professional with an experience of more than 6 years in Automotive and Consumer Appliance Industry. Effective communicator with excellent management and analytical skills with attention to detail, good team player and flexible working in a fast-paced environment. Architected Artificial Intelligence applications with Machine Learning and Deep Learning using Python. Implemented Machine Learning techniques such as linear/logistic regression, ensemble methods like Random forest and XGBoost as well as K-Nearest Neighbours, Naive Bayes Classifier, SVM and Clustering algorithms like K-means to solve various business problems across multiple domains like Banking, Finance and Healthcare in addition to Consumer industry. Leveraged Deep Learning techniques like ANN, CNN and transfer learning to create Fabric Detection models for better classification. Used RNN-LSTM, Encoders & Decoders, Attention models and State of the art Transformers & BERT techniques to develop Language models and develop conversational AI with Google Dialogflow Chatbot. Skilled in libraries such as Sklearn, Numpy, Pandas, Tensorflow, Keras, Pytorch and Matplotlib, Seaborn for Data Visualization. Extensive knowledge of working with NoSQL databases like Mongodb and SQL databases like MySQL and PostgreSQL for effective and faster data querying and extraction. Worked Independently for deployment of Models using Google Kubernetes Engine. Implemented Flask framework with Flassger for Web API creation followed by deployment in Heroku(PaaS). Developed a Web Application for IPL (Indian Premier League) Prediction of Cricket First Innings score based on historic data using lasso regression technique and deployed using Flask framework on Heroku Platform (PaaS). Contributor to the Data Science Community through Kaggle and Github and avid reader of Medium articles. ©