Technical Blog Series: Causal ML & LLM Fine-Tuning

Ordered deep-dive series for ML engineers: causal inference (SCM, IPS) and production LLM fine-tuning (SFT, LoRA, QLoRA, DPO, multi-adapter).

SERIES · 2 PARTS

Causal Machine Learning: Prediction to Intervention

Structural causal models, backdoor adjustment, and IPS for production decision systems.

  1. 01Why Machine Learning Demands Causal Inference
  2. 02Fixing Selection Bias in Enterprise Data with Inverse Propensity Scoring (IPS)
Open series
Causal Machine Learning: Prediction to Intervention

SERIES · 5 PARTS

Model Fine-Tuning: SFT, LoRA, QLoRA & DPO

End-to-end LLM adaptation: PEFT, QLoRA, preference alignment, and multi-adapter serving.

  1. 01The Definitive Guide to LLM Fine-Tuning: Objectivee, Mechanisms, and Hardware
  2. 02Deconstructing LoRA: The Math and Mechanics of Low-Rank Adaptation
  3. 03A Technical Guide to QLoRA and Memory-Efficient Fine-Tuning
  4. 04Aligning LLMs with Direct Preference Optimization (DPO)
  5. 05Building LoRA Multi-Adapter Inference on AWS SageMaker
Open series
Model Fine-Tuning: SFT, LoRA, QLoRA & DPO

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