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Machine-Learning-Tokyo

papers-with-annotations

Research papers with annotations, illustrations and explanations

TutorialsML/AI fundamentals
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创建于 2020-06-01 · 更新于 2026-08-31 · 今日第 13413 名
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alisher-aij-cunanan

Machine-Learning-Tokyo/papers-with-annotations 排名第 13,413，有 827 个星标。

同类别比较

Machine-Learning-Tokyo/papers-with-annotations 排名第 13,413，此处有 8 个同类条目；jingtian11/EasyOffer 排名第 13,418。

同类别比较
名称排名指标
YixinChen-AI/CVAE-GAN-zoos-PyTorch-Beginner13,372
语言:
Python
星标数:
831
分叉数:
116
简介:
For beginner, this will be the best start for VAEs, GANs, and CVAE-GAN. This contains AE, DAE, VAE, GAN, CGAN, DCGAN, WGAN, WGAN-GP, VAE-GAN, CVAE-GAN. All use PyTorch.
openai/model_spec13,377
星标数:
831
分叉数:
104
简介:
The OpenAI Model Spec
databricks-academy/large-language-models13,385
语言:
Python
星标数:
830
分叉数:
465
简介:
Notebooks for Large Language Models (LLMs) Specialization
firecrawl/firecrawl-app-examples13,398
语言:
Jupyter Notebook
星标数:
829
分叉数:
213
简介:
🔥 This repository contains complete application examples, including websites and other projects, developed using Firecrawl.
jingtian11/EasyOffer13,418
语言:
Jupyter Notebook
星标数:
827
分叉数:
56
简介:
《EasyOffer》（<大模型面经合集>）是针对LLM宝宝们量身打造的大模型暑期实习Offer指南，主要记录大模型暑期实习和秋招准备的一些常见大厂手撕代码、大厂面经经验、常见大厂思考题等；小白一个，正在学习ing......有问题各位大佬随时指正，希望大家都能拿到心仪Offer！
EvilPort2/Sign-Language13,422
星标数:
826
分叉数:
357
简介:
A very simple CNN project to recognize gestures made in American Sign Language
NVIDIA/TileGym13,423
语言:
Python
星标数:
826
分叉数:
92
简介:
Helpful kernel tutorials, examples and SKILLs for tile-based GPU programming
wenxinxu/resnet-in-tensorflow13,440
语言:
Python
星标数:
825
分叉数:
274
简介:
Re-implement Kaiming He's deep residual networks in tensorflow. Can be trained with cifar10.
关键参数与规格
关键参数与规格
参数值
类别Tutorials
子类别ML/AI fundamentals
星标数827
分叉数75
贡献者2
创建日期2020-06-01
更新日期2026-08-31
1 天星标数0
7 天星标数0
排名13,413
上次排名13,316
排名变化-97
7 天星标排名13,928
上次 7 天星标排名13,947
7 天星标排名变化19
总星标排名12,972
上次总星标排名12,956
总星标排名变化-16
国家Japan
README 摘录

Papers with Annotations (PwA) (created by Alisher Abdulkhaev. Twitter | LinkedIn | GitHub | alisher@mltokyo. ai) This project compiles multiple (AI-related) papers with illustrations, annotations, and brief explanations for technical keywords, terms and previous studies which makes them easier to read and to get the main idea intuitively. object detection PwA ai and cognitive science related PwA unsupervised and semi/self-supervised learning related PwA convolutional neural networks related PwA miscellaneous PwA Please feel free to open new PR (pull request

) if you have such kind of annotated research papers (related to AI, ML, DL, neuroscience, cognitive sciences). Also, please give us a feedback by opening an issue on this repository. We are looking forward for your collaboration! 📌 **Hardware:** iPad (6th generation) with Apple Pencil (1st generation). However, any iPad (which supports Apple pencil) or any Android tablets should be fine. Featured at: 📌 MLT's Blog 📌 David Ha's tweet 📌 www. com Contributors: Alisher Abdulkhaev Jayson Cunanan

常见问题

记录了多少星标和分叉？

Machine-Learning-Tokyo/papers-with-annotations 有 827 个星标和 75 个分叉。

仓库排名是多少？

Machine-Learning-Tokyo/papers-with-annotations 排名第 13,413。

哪个仓库排名最接近？

Machine-Learning-Tokyo/papers-with-annotations 与 jingtian11/EasyOffer 比较，后者排名第 13,418，有 827 个星标。

README

Papers with Annotations (PwA)

(created by Alisher Abdulkhaev. Twitter | LinkedIn | GitHub | alisher@mltokyo.ai)

This project compiles multiple (AI-related) papers with illustrations, annotations, and brief explanations for technical keywords, terms and previous studies which makes them easier to read and to get the main idea intuitively.

Please feel free to open new PR (pull request) if you have such kind of annotated research papers (related to AI, ML, DL, neuroscience, cognitive sciences).

Also, please give us a feedback by opening an issue on this repository. We are looking forward for your collaboration!

Annotation tools:

How are the annotations generated:

📌 Software: Notability App — import pdf to the App, make annotations (handwriten notes, import the figures, stickers, etc) and export the pdf.

📌 Hardware: iPad (6th generation) with Apple Pencil (1st generation). However, any iPad (which supports Apple pencil) or any Android tablets should be fine.

Featured at:

📌 MLT's Blog

📌 David Ha's tweet

📌 www.analyticsvidhya.com

Contributors:

  • Alisher Abdulkhaev
  • Jayson Cunanan
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