TranslatedChinese translation of 《Designing Data-Intensive Application》 (DDIA), 1st edition / 2nd edition
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🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
- bloom
- deep-learning
- distributed-systems
- language-models
TranslatedOpen-source manuscript of 《深入理解 AI Infra:量化分析与系统设计》 (In-Depth Understanding of AI Infra: Quantitative Analysis and System Design), by 李博杰 (Li Bojie): starting from hardware constraints and model architecture, it quantitatively derives the system design of LLM inference and training. Includes the full text of the book, a PDF, and companion calculation tools and experiments
- accelerator
- ai-infra
- ai-infrastructure
- book
Python Stream Processing
- kafka-streams
- kafka
- python
- asyncio
Asynchronous Python framework for event-driven services. A thin client for Kafka, RabbitMQ, NATS, Redis and MQTT with full access to native broker features, plus AsyncAPI docs, in-memory tests and observability out of the box.
Python Stream Processing. A Faust fork
A library for event sourcing in Python.
- domain-driven-design
- ddd
- eventsourcing
- cqrs
Stream Processing Made Easy
- machine-learning
- reactive-programming
- kafka
- reactive-systems
Conflict-free merge for DataFrames, JSON, ML models & distributed agents — powered by CRDTs. The first merge library where every operation is mathematically guaranteed to converge.
- collaborative-editing
- conflict-resolution
- crdt
- data-engineering