MLWhiz: Recs|ML|GenAI

MLWhiz: Recs|ML|GenAI

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Crack ML System Design Interviews Like a Pro - Part 1
Real Stories, Real Strategies: An Interviewer's Guide to what Actually Works
Pretraining 101: Data, Scale, and the Loss Function
GenAI Fundamentals Series Part 4: How a pile of random weights becomes a base model. Next-token cross-entropy, trillion-token data pipelines, and…
HSTU From Scratch in PyTorch - A complete Walkthrough
RecSys for MLEs Part 9d: data pipeline, three sub-layers, retrieval + rating loss, and benchmarking against rectools' HSTU on MovieLens-1M
MLWhiz Weekly Recsys/ML/GenAI Newsletter # 11 - The week US government pulled a frontier model offline on a letter
Trump Strikes!!!
Post-Training 101: From Base Model to Assistant
genAI Fundamentals Part 5: instruction tuning (SFT), RLHF vs DPO, and the RLVR/GRPO reasoning era — how a base model learns to follow instructions and…
Subscribe to get my Free Advanced Python Book
The people who always seem ahead of the curve? They have one thing in common. This inbox.

GenAI Fundamentals

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Post-Training 101: From Base Model to Assistant
genAI Fundamentals Part 5: instruction tuning (SFT), RLHF vs DPO, and the RLVR/GRPO reasoning era — how a base model learns to follow instructions and…
Pretraining 101: Data, Scale, and the Loss Function
GenAI Fundamentals Series Part 4: How a pile of random weights becomes a base model. Next-token cross-entropy, trillion-token data pipelines, and…
What is an LLM? Tokens, Embeddings, and the Big Picture
GenAI Fundamentals Series Part 3: From raw text to next-token prediction. The complete mental model
The Transformer, Demystified — Let's Actually Build One
GenAI Series Part 2: Implementing a Transformer

Recsys

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HSTU From Scratch in PyTorch - A complete Walkthrough
RecSys for MLEs Part 9d: data pipeline, three sub-layers, retrieval + rating loss, and benchmarking against rectools' HSTU on MovieLens-1M
HSTU: How Meta Built a Trillion-Parameter Recommender That Actually Scales
The architecture, the math, the code, and why every RecSys team is suddenly building one
From Random IDs to Semantic IDs: Building a Generative Recommender from Scratch
How RQVAE compresses item embeddings into meaningful tokens, enabling TIGER-style generative recommendation. Full code walkthrough on Steam Games with…
From RNNs to Transformers: Building Sequential Recommenders (Part 1)
RecSys Series Part 9a: Implementing GRU4Rec and SASRec on Steam Games — with production deployment patterns

ML Careers

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Claude Code vs. Your ML Career: A 2026 Reality Check
The ML job market didn't die. It split into two — here's how to land on the right side.
How to Crack FAANG Coding Interviews?
The pattern-based approach that transforms coding interviews from impossible puzzles into recognizable problems
Crack ML System Design Interviews Like a Pro - Part 2
Netflix Real-World Case Study
Crack ML System Design Interviews Like a Pro - Part 1
Real Stories, Real Strategies: An Interviewer's Guide to what Actually Works

Generative AI

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I Use Claude Code Every Day. Here's the Setup That Actually Matters
CLAUDE.md, Skills 2.0, permission modes, channels — an opinionated guide for beginners and the mildly curious
What Production Deployments Taught Me About ReAct vs Function Calling
From Prototype to Production: Hard-Won Lessons for AI Agent Development
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
Which AI Subscription is Actually Worth Your Money?
The Real-World Guide for Developers and Non-Developers alike

Newsletter

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MLWhiz Weekly Recsys/ML/GenAI Newsletter # 11 - The week US government pulled a frontier model offline on a letter
Trump Strikes!!!
MLWhiz Weekly Recsys/ML/GenAI Newsletter # 10 - The week AI infrastructure crossed from a technology story to a financial one
Hey, Rahul here!
MLWhiz Weekly Recsys/ML/GenAI Newsletter # 9 - The week AI started its IPOs
The AI industry is about to stop being a private market story. Quarterly earnings calls ask harder questions than venture capitalists.
MLWhiz Weekly Recsys/ML/GenAI Newsletter # 8 - The week of Google I/O 2026
Google I/O opened up a lot of eyes for major AI firms

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Making ML careers accessible and GenAI, Recsys, and MLOps understandable. 🔧 No-fluff guides and real-world insights to help you build, deploy, and advance in the machine learning and Generative AI ecosystem
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MLWhiz: Recs|ML|GenAI

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