haaaguro Goto Github PK

airtest

UI Automation Framework for Games and Apps

awesome-speech-enhancement

A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.

awesome-speech-recognition-speech-synthesis-papers

Speech synthesis, voice conversion, self-supervised learning, music generation,Automatic Speech Recognition, Speaker Verification, Speech Synthesis, Language Modeling

chinesenre

中文实体关系抽取，pytorch，bilstm+attention

cs-books

🔥🔥超过1000本的计算机经典书籍、个人笔记资料以及本人在各平台发表文章中所涉及的资源等。书籍资源包括C/C++、Java、Python、Go语言、数据结构与算法、操作系统、后端架构、计算机系统知识、数据库、计算机网络、设计模式、前端、汇编以及校招社招各种面经~

cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

densenet.pytorch

A PyTorch implementation of DenseNet.

dlaicourse

Notebooks for learning deep learning

fast-transformers

Pytorch library for fast transformer implementations

fgoassetsmodifytool

Fate/GO资源解密工具

fks

前端技能汇总 Frontend Knowledge Structure

google-research

Google Research

grasscutter

A server software reimplementation for a certain anime game.

hentaianimedown

imageprocessing100wen

「画像処理100本ノック」中文版本！为图像处理初学者设计的 100 个问题。

java-interview

「Java面试小抄」一份通向理想互联网公司的面试汇总，包括 Java基础、Java并发、JVM、MySQL、Redis、Spring、MyBatis、Kafka、计算机操作系统、计算机网络、系统设计、分布式、Java 项目实战等

javaguide

「Java学习+面试指南」一份涵盖大部分Java程序员所需要掌握的核心知识。

jellyfin-plugin-template

Plugin Template for Jellyfin

limes

Link Discovery Framework for Metric Spaces.

local-attention

An implementation of local windowed attention for language modeling

militarykg

mircorts

mlbooks

机器学习的相关书籍

mlofandrew-ng

吴恩达机器学习课程的讲义，欢迎大家一起学习

pytorch-kaldi

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

reformer-pytorch

Reformer, the efficient Transformer, in Pytorch

seu_monash_2017-2018

Helpful and available for students of SEU-Monash in Suzhou

tensorflow2.0-examples

🙄 difficult algorithm, simple code.

traditional-speech-enhancement

Spectral Subtraction, Wiener Filtering, MMSE