Nihar Shetty
Data Scientsit Intern
Irvine,CA
Overview
1
1
year of professional experience
1
1
Certification
Work History
Data Scientist Intern
Eitacies
08.2022 - 07.2023
- Developed proof-of-concept project using Machine Learning to track real-time video meetings in collaboration with cross-functional teams.
- Processed data for sentiment analysis of video frames, including extraction, preprocessing, and mining.
- Increased storage capacity by 400% by reducing frame redundancy and optimizing storage
- Verified machine learning model with external and edge test cases.
- Analyzed facial expressions in images using DeepFace library and pre-trained deep learning models.
- Implemented loop to analyze multiple images, extracting and printing dominant emotion for each image
Education
Master of Science - Information Technology
Arizona State University
Tempe, AZ05.2023
Bachelor of Science - Computer Science
Nitte Meenakshi Institute of Technology
Bangalore, India09.2020
Skills
- Technical Skills
- Languages: Python, SQL,Scala, C
- Skills: Data Mining, Data Visualization, Data Preprocessing, Natural Language Processing, Machine Learning, Deep Learning, Artificial Intelligence, Computer Vision, Unsupervised Learning, Supervised Learning, Statistics
- Data Storage: SQL Server Management Studio, Couchbase, MongoDB, AWS DynamoDB, Hadoop
- Libraries NumPy, Pandas, PyTorch, TensorFlow, NLTK, OpenCV
- Cloud: AWS VPC, AWS LightSail, AWS S3, Route53
- Tools: Tableau, Jupyter Notebook, Microsoft Excel, Microsoft Projects, Databricks
Accomplishments
Cafe Website on AWS
•Hosted an example cafe website on an EC2 instance in multiple availability zones and connected it with an elastic load balancer and an auto scaling group to achieve high fault tolerance, high availability and scalability
•Configured security groups and network access control lists for limited access to the backend systems.
•For order processing, the EC2 instances were configured to connect to AWS Relational Database Service (RDS).
SentimentLens: Sentiment Analysis for Product Reviews
•Successfully led an MLOPS project for sentiment analysis, developing a robust NLP-based model and implementing automated deployment using Docker and Kubernetes.
•Established continuous integration and monitoring pipelines, ensuring high code quality and accurate performance tracking. The model achieved an F1 score of 0.85 and an accuracy of 87% on the test dataset, while incorporating user feedback for iterative model updates.
•Demonstrated effective collaboration with cross-functional teams, achieving seamless workflows and delivering a reliable sentiment analysis solution with improved accuracy over time.
Telecommunication Churn Prediction
•Designed a decision tree model to predict churn in a telecommunication company utilizing PySpark in Databricks.
•Preprocessed data and eliminated null values, irrelevant features and additionally executed one hot encoding on data.
•Formulated a data processing pipeline containing DecisionTree Classifier, VectorIndexer, StringIndexer which predicted overall churn rate achieving an accuracy of 86.6%.
Certification
Azure Databricks for Data Engineering Certificate from Microsoft (Coursera, 2023)
Timeline
Data Scientist Intern
Eitacies
08.2022 - 07.2023
Master of Science - Information Technology
Arizona State University
Bachelor of Science - Computer Science
Nitte Meenakshi Institute of Technology
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