sejalv,Sejal Vaidya,github

💼 Bio

Data generalist, with 13+ years of experience in Data/ML Platforms and Software Engineering, across Healthcare, Digital Health and Wellbeing, and e-Commerce sectors. Proficient in MLOps & Cloud architectures, agile management for data science, data-driven decision making, and fostering empathic collaboration with diverse & cross-functional teams to ensure alignment & scalability. Research-driven, analytical & adaptable.
Most recently worked on MLOps -specific areas such as Experimentation tooling, infrastructure for Model Deployment & Monitoring, and applying Software Engineering/DevOps practices across the ML lifecycle
More info here: LinkedIn | DataTalks.Club | Medium

📢 Independent & Community contributions:

DataTalks.Club

Co-Instructor for DTC's MLOps Engineering Zoomcamp (2022-Present): Repo | Videos
Co-Instructor for DTC's Data Engineering Zoomcamp (2022): Repo | Videos
Podcast interview for DTC mini's: Data Engineering to MLOps (2021)
Workshop on Containerized ML deployment with AWS Lambda (2020): Repo | Video | Article

Misc

Podcast interview: Data Engineering Confessions with Pipeline Data Engineering Academy (2020)
Article: SQL in a Nutshell, published in Towards Data Science

Sejal Vaidya's Projects

cd4ml-scenarios

Repository with sample code and instructions for "Continuous Intelligence" and "Continuous Delivery for Machine Learning: CD4ML" workshops

customer_analytics_dwh_and_queries

Basic data model for an e-commerce, with SQL queries providing customer insights

data-engineering-zoomcamp

Code for Data Engineer Zoomcamp course

hadoop_poc

IMDB ANALYSIS – A PROOF OF CONCEPT ON BIG DATA AND HADOOP

ml-monitoring

A demo of Prometheus+Grafana for monitoring an ML model served with FastAPI.

mlops-zoomcamp

Free MLOps course from DataTalks.Club

movierec

Movie Recommendations Website, that lets you rate/review movies and accordingly generates recommendations for you

python_spark_bigd_ml

Spark examples, personal projects with Python, Spark Streaming, Machine Learning, Spark DataFrames

serverless-ml-workshop

Deployment of ML models with Serverless APIs (AWS Lambda) and Docker

solarsys_sv

Service to send a daily email, highlighting hours of the day when solar DC power was less than 80% of reference DC power data

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