zhoukaiwei66's Stars
jackfrued/Python-100-Days
Python - 100天从新手到大师
MisterBooo/LeetCodeAnimation
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)
scikit-learn/scikit-learn
scikit-learn: machine learning in Python
ageitgey/face_recognition
The world's simplest facial recognition api for Python and the command line
Avik-Jain/100-Days-Of-ML-Code
100 Days of ML Coding
apachecn/ailearning
AiLearning:数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
lib-pku/libpku
贵校课程资料民间整理
terryum/awesome-deep-learning-papers
The most cited deep learning papers
MLEveryday/100-Days-Of-ML-Code
100-Days-Of-ML-Code中文版
fengdu78/lihang-code
《统计学习方法》的代码实现
nndl/nndl.github.io
《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning
virgili0/Virgilio
Your new Mentor for Data Science E-Learning.
MorvanZhou/tutorials
机器学习相关教程
mrgloom/awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
TA-Lib/ta-lib-python
Python wrapper for TA-Lib (http://ta-lib.org/).
SmirkCao/Lihang
Statistical learning methods, 统计学习方法(第2版)[李航] [笔记, 代码, notebook, 参考文献, Errata, lihang]
apachecn/sklearn-doc-zh
:book: [译] scikit-learn(sklearn) 中文文档
OUCMachineLearning/OUCML
huaxz1986/cplusplus-_Implementation_Of_Introduction_to_Algorithms
《算法导论》第三版中算法的C++实现
weiaicunzai/awesome-image-classification
A curated list of deep learning image classification papers and codes
geekinglcq/CDCS
Chinese Data Competitions' Solutions
YouChouNoBB/2018-tencent-ad-competition-baseline
2018腾讯广告算法大赛baseline 线上0.73
ZJULearning/MatlabFunc
Matlab codes for feature learning
sml2h3/mmewmd_crack_for_wenshu
文书网MmEwMd参数破解,2023.06.25供应文书一手日更数据
xingbuxing/TA-Lib-in-chinese
中文版TA-Lib库使用教程
MLjian/TextClassificationImplement
’达观杯‘文本智能处理挑战赛,文本分类任务的实现,包括一些传统的监督学习算法和深度学习算法,主要基于sklearn/xgb/lgb/pytorch包实现。
mlapin/libsdca
Multiclass classification based on stochastic dual coordinate ascent
gionuno/arc_cosine_kernels
Experimentation with arccosine kernels, with a softmax perceptron for classification, and a use of isomap. Based on the paper Kernel Methods for Deep Learning by Youngmin Cho and Lawrence K. Saul.