Books

Large Language Models at Work

Large Language Models at Work is a book about leveraging large language models in software solutions.

Excerpts

• N-shot Learning
• Embeddings and Vector Databases
• Interacting With External Systems
• Planning
• Adversarial LLM Attacks

---

Data Engineering on Azure

Data Engineering on Azure reveals the architectural, operational, and data management techniques that power cloud-based data infrastructure built on the Microsoft Azure platform.

Excerpts

• Changing data classification through processing
• Ingesting data
• Machine Learning on Azure - part 1
• Machine Learning on Azure - part 2
• Machine Learning on Azure - part 3

---

Programming with Types

Programming with Types teaches you to design safe, resilient, correct software that's easy to maintain and understand by taking advantage of the power of strong type systems.

Excerpts

• A switchless state machine
• Common algorithms
• Higher kinded types: functors
• Higher kinded types: monads
• Variance

---

Articles

For Data Science @ Microsoft

• How we built self-serve data environment tools with Azure
• Azure Data Explorer at the Azure business scale
• Running machine learning at scale
• Common data engineering challenges and their solutions
• Partnering for data quality
• Partnering for metadata management
• Data distribution

Computability Series

• A short history
• Turing machines
• Tag systems
• Conway's game of life
• Elementary cellular automata
• Von Neumann architecture
• Machine implementation practicalities
• Lambda calculus
• LISP

Mental Poker Series

• Mental Poker
• Mental Poker Part 0: An Overview
• Mental Poker Part 1: Cryptography
• Mental Poker Part 2: Fluid Ledger
• Mental Poker Part 3: Transport
• Mental Poker Part 4: Actions and Async Queue
• Mental Poker Part 5: State Machine
• Mental Poker Part 6: Shuffling Implementation
• Under development, more to come...