Best of Daily Dose of Data Science | Avi Chawla | Substack — December 2025

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   Daily Dose of Data Science | Avi Chawla | Substack·16w

   The AI Engineering Guidebook

   A comprehensive 350+ page guidebook covering the engineering fundamentals of LLM systems, including model architecture, training, prompt engineering, RAG systems, fine-tuning techniques like LoRA, AI agents, Model Context Protocol, optimization strategies, and deployment considerations. The resource focuses on practical engineering decisions, system design tradeoffs, and real-world implementation patterns rather than surface-level usage.

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   Daily Dose of Data Science | Avi Chawla | Substack·18w

   Finally, MCP Servers Can Deliver UI-rich Experiences!

   MCP servers traditionally only return text/JSON responses without UI capabilities. The open-source mcp-use framework solves this by letting developers create React components that automatically register as MCP tools and render as interactive widgets in ChatGPT. Components placed in a resources/ folder become callable tools with zero boilerplate—no duplicate schemas or manual registration needed. The framework supports the full React ecosystem, hot reloading, and automatic theme syncing with ChatGPT's light/dark mode. A practical example demonstrates building an interactive stock chart widget that displays closing prices over time.

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   Article

   Daily Dose of Data Science | Avi Chawla | Substack·16w

   [Hands-on] Deploy and Run LLMs on your Phone!

   Fine-tune and deploy LLMs directly on iOS and Android devices using UnslothAI, TorchAO, and ExecuTorch. The tutorial walks through loading Qwen3-0.6B, preparing reasoning and chat datasets, training with quantization-aware methods, exporting to mobile-ready .pte format, and running the model locally on iPhone at ~25 tokens/second. The resulting model is ~470MB and runs 100% on-device without requiring cloud connectivity.

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