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University College Cork
- Electrical and Electronic Engineering, University College Cork, COLLEGE ROAD, CORK
- https://www.ucc.ie/en/
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Starred repositories
《Hello 算法》:动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新,English version ongoing
Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners
PyTorch implementation of MAE https//arxiv.org/abs/2111.06377
深度学习入门教程, 优秀文章, Deep Learning Tutorial
Demonstrate all the questions on LeetCode in the form of animation.(用动画的形式呈现解LeetCode题目的思路)
Linux命令大全搜索工具,内容包含Linux命令手册、详解、学习、搜集。https://git.io/linux
A collection of awesome LaTeX Thesis/Dissertation templates and beyond! (LaTeX / Word / Typst / Markdown 格式的学位论文、演示文稿、报告、项目申请书、简历、书籍等模板收藏)
Natural Language Processing Tutorial for Deep Learning Researchers
Notes about courses Dive into Deep Learning by Mu Li
MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
An implementation of Conformer: Convolution-augmented Transformer for Speech Recognition, a Transformer Variant in TensorFlow/Keras
[Unofficial] PyTorch implementation of "Conformer: Convolution-augmented Transformer for Speech Recognition" (INTERSPEECH 2020)
Implementation of the convolutional module from the Conformer paper, for use in Transformers
Code examples in pyTorch and Tensorflow for CS230
100-Days-Of-ML-Code中文版
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep N…
The fastai book, published as Jupyter Notebooks
This is Andrew NG Coursera Handwritten Notes.
PyTorch tutorials, examples and some books I found 【不定期更新】整理的PyTorch 最新版教程、例子和书籍
A resource for learning about Machine learning & Deep Learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
A playbook for systematically maximizing the performance of deep learning models.