I am AWS certified Machine Learning Specialist with 5 years of analytical experience. A strategic mindset that focuses on problem-solving tasks and maintaining priorities on strict deadlines.
Experience
I have 5 years of experience as Data Analyst. During my career, I used Python to analyze data, create visualizations using Tableau, and created data pipeline from on-premise data to AWS using AWS Kinesis.
I have been part of the team responsible for handling end to end data operations from streaming on premise data to AWS cloud storage, performing Analysis on the data using Python libraries, making actionable insights using Tableau and developing predictive models using the machine learning algorithms in Python scikit-learn library and also using AWS SageMaker.
Projects
I have worked on multiple machine learning and deep learning projects.
Sports Image Classifier – RESNET 50, CNN, AWS SageMaker, S3 • Created and deployed a classifier using CNN to classify sports images. • Created my own dataset of images with labels, hosted them on the S3 and used Amazon SageMaker to train the RESNET 50 model with transfer learning of ImageNet data with an accuracy of 97%. • Deployed the model as a web application on render.
Capture Streaming Data – AWS Kinesis Streams, CloudFormation, S3, Lambda, QuickSight • Created a pipeline for streaming data and performed transformations and stored the result in JSON format in S3 using Lambda. • Captured streaming data using Kinesis Data Stream, performed transformation using SQL queries in Analytics stream and delivered the JSON data to S3 using Firehose. Visualized this data using AWS QuickSight.