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193–216 of 1,009 · Most stars

Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀

  • dataframe
  • python
  • bigdata
  • tabular-data

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy

  • json
  • python
  • rust
  • serialization

[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation

  • depth-estimation
  • image-synthesis
  • metric-depth-estimation
  • monocular-depth-estimation

Ingest, parse, and optimize any data format ➡️ from documents to multimedia ➡️ for enhanced compatibility with GenAI frameworks

  • ingestion-api
  • ocr
  • omniparser
  • parse-server

TranslatedA knowledge graph for mathematics (primary school to high school), English (grade 3 to high school), and junior high school physics: 1,644 knowledge points, 2,403 prerequisite edges, and 6,723 questions, aligned with the curriculum standards, with an adaptive prerequisite diagnostic.

  • chinese
  • curriculum
  • diagnostic
  • edtech

Translated⛽️ "Algorithm Clearance Handbook": A learning tutorial on "algorithms and data structures" starting from zero, with 200 "popular algorithm interview questions" and 1000+ "LeetCode problem analyses", continuously updated!

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