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MLWhiz Weekly AI/ML Newsletter # 1
Here is what happened this week.
Mar 11
•
Rahul Agarwal
February 2026
Vector Search at Scale: The Production Engineer's Guide
IVF partitions space. PQ compresses memory. Together they make 100M vector search actually possible
Feb 3
•
Rahul Agarwal
6
3
January 2026
How YouTube Finds Your Next Video in Milliseconds
A deep dive into two-tower retrieval, in-batch negatives, and the tricks that make it work
Jan 26
•
Rahul Agarwal
3
2
The 3-Stage Funnel Behind Every Modern Recommender System
Two-Tower models, vector databases, cross-encoders—and how they work together at scale
Jan 20
•
Rahul Agarwal
14
6
October 2025
How Recommendation Systems Learned to Think
Recsys Series Part 2: From collaborative filtering breakthroughs to generative AI agents that can chat about your preferences and explain their…
Oct 4, 2025
•
Rahul Agarwal
9
3
September 2025
RecSys Fundamentals: The Art and Science of Digital Matchmaking
Recsys Series Part 1: Master the three core approaches that power every modern recommendation engine
Sep 27, 2025
•
Rahul Agarwal
12
8
What Production Deployments Taught Me About ReAct vs Function Calling
From Prototype to Production: Hard-Won Lessons for AI Agent Development
Sep 21, 2025
•
Rahul Agarwal
6
2
July 2025
The 5 Principles That Turn ML Projects Into Business Impact
Why 70% of machine learning projects fail to deliver value, and the engineering-first approach that ensures yours won't be one of them
Jul 18, 2025
•
Rahul Agarwal
2
1
The #1 Reason Your GenAI Project Will Fail in Production (and the 4 Pillars to Prevent It)
A Technical Guide to Overcoming Operational Nightmares and Exploding Costs in LLM Deployments
Jul 9, 2025
•
Rahul Agarwal
6
5
Which AI Subscription is Actually Worth Your Money?
The Real-World Guide for Developers and Non-Developers alike
Jul 3, 2025
•
Rahul Agarwal
13
4
What is GraphRAG and how it works
From Scattered Facts to Connected Intelligence
Jul 1, 2025
•
Rahul Agarwal
6
1
3
June 2025
How to Crack FAANG Coding Interviews?
The pattern-based approach that transforms coding interviews from impossible puzzles into recognizable problems
Jun 20, 2025
•
Rahul Agarwal
12
6
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