Graduate Student @ 
I passionately study and work on the entire machine learning lifecycle starting from data acquistaion to deployment and monitoring of the model. I have spent quality time on my projects in cleaning data, wranginling data, creating visuals and communicating the insights as a story easy to follow. Demonstrated experience completing data science projects and deploying machine learning models (Azure, GCP, AWS). I also have extensive expereince in building CI/CD and data pipelines with tools like AirFlow, Kafka, Terraform, Docker, Kubernetes. I belive in making my data science work better by combining my software enginnering skills (DS, Algos, Unit and Integration Tests).
Python: pandas, sklearn, nltk, huggig face, tensorflow, tensorboard, beautiful soup, pytest
SQL : MySQL, MS-SQL SERVER, POSTGRES
NoSQL : mongoDB
Tools : Airflow, Kafka, Comet-ML, MLFLOW,
Data Visuzalization: Tabeleu, matplotlib, seaborn,
Cloud Tech: Azure, AWS and GCP
Statistics: Hypothesis testing, A/B Testing, Probablity
- Using Hugging Face Transformers
- Identifying an author based on text excrepts
- Chat Bot with RASA and Tensorflow
- Deploying Machine Learning Application with Docker
- Deploying Visualization and Monitoring using Graphite and Grafana
- Machine Learning and Deep Learning.
- Machine Learning Enginerring Platform (MLOps)
- Data Drift Detection
- Telling visual stories using data (Tabeleu, python notebooks, comet-ml)
- Build and publish Machine learning/ Deep learning models for (hackathons/ my passion projects/) with comments and report my findings.
- Practice and Publish my Learnings in building data pipelines for Building ML/DL models.
- Host my code for the articles I publish at medium
- Learn and code cutting edge Deep Learning methods/models.