Insights on Data Science, Machine Learning, and Software Engineering
Deep dive into architecting an end-to-end ML pipeline that processes 40K+ images with 92% accuracy using ResNet-50 and dimensionality reduction techniques.
Lessons learned from building production-grade data systems that serve 50K+ users with 99.9% uptime using MongoDB, PostgreSQL, and Redis.
How I built a personalized LLM on iOS using Google PaLM 2 and CoreML, achieving 85% query resolution rate. Research Excellence Award recipient.
A practical guide to deploying machine learning models at scale, covering Docker, Kubernetes, monitoring, and A/B testing strategies.
Building predictive models that reduced carrying costs by $75K annually through analyzing 1M+ sales records using Python and statistical techniques.
Designing and deploying microservices that handle 10K+ concurrent requests with 65% latency reduction using Redis caching and optimization.
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