Working as a Data Science Trainee.

Explored Django completely end to end and worked on multiple use cases like creating a custom blogging website [Details] and an ecommerce website [Details].

Explored Django Rest API framework.

Worked on deploying Django projects on AWS EC2.

Explored AWS RDS and Lambda Function.

Worked as a Data Science Intern.

Involved in data pre-processing techniques for making the data useful for creating Machine Learning models.

Translated product requirements to analytical requirements/specifications, design and develop required functionality.

Experienced architecting Artificial Intelligence applications with Machine Learning and Deep Learning with Python. Deep Learning Techniques included ANN, CNN, RNN, Advanced CNN and Advanced RNN with LSTM.

Explored Machine Learning and Deep Learning libraries like Scikit-learn, Xgboost, PySpark, Tensorflow, Keras and Pytorch.

Completed an end to end project implementing MLOPS to determine whether a customer is placing fraudulent vehicle insurance claim. Entire workflow deployed on Google Cloud Platform using Flask.[Details]

Took part in the rotational internship program on Data Science and Business Analytics.

Reviewed, analysed and implemented data requirements effectively by creating supervised and unsupervised algorithms based on deep dive statistical analysis and predictive data modelling.

Explored Business Analytics.

Completed the capstone project implementing Machine Learning Regression technique to predict the likelihood of a student passing an examination.[Details]