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I am Riz.

Are you interested in machine learning or data science? You may be here for my ML & DS Fundamentals, my Publications, or my Systems work.

I'm an ML and AI enthusiast with experience in software and cloud systems. I hold an MS in Computer Science from SEMO and am currently pursuing an MS in AI from UT Austin.

I share what I've learned through:

• ML & DS Fundamentals — Visual guides on the mathematical foundations of ML. Topics include Probability, Bayes' Theorem, Random Variables & Distributions, Statistics, Information Theory, and Compound Probability. Each is a standalone interactive guide with worked examples tied to real ML practice.

• Publications — Research from graduate studies spanning computer vision, NLP, and systems. Includes Sketch Classification with CNNs on 250-class recognition, Image Recognition with Classical ML using HOG + SVM, Senator Tweet Analysis covering NLP on 419K+ tweets, and three more papers on ASL translation, healthcare cloud, and security scanning.

• Systems — Software design patterns, distributed systems, and API architecture — the infrastructure layer beneath ML systems. Covers topics like queue-based stage decoupling, ingest-transform-serve pipelines, memory allocation, session window feature engineering, and 30+ more posts on algorithms, data structures, and microservices.

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