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This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

  • deep-learning
  • tensorflow-examples
  • convolutional-neural-networks
  • recurrent-neural-networks

An Open-Source Python3 tool with SMALL models for recognizing layouts, tables, math formulas (LaTeX), and text in images, converting them into Markdown format. A free alternative to Mathpix, empowering seamless conversion of visual content into text-based representations. 80+ languages are supported.

  • math-formula
  • ocr
  • latex
  • math-formula-recognition

An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) for key-frame segmentation and Associating Objects with Transformers (AOT) for efficient tracking and propagation purposes.

  • interactive-segmentation
  • segment-anything
  • segment-anything-model
  • video-object-segmentation

Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021, T-PAMI 2022

  • feature-matching
  • pose-estimation
  • 3d-vision

An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈

  • ai-pipelines
  • approximate-statistics
  • statistical-properties
  • data-quality

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

  • gat
  • graph-attention-networks
  • attention-mechanism
  • self-attention

Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.