Zhibo Tian's repositories
Co-teaching_python3
This the python3 version of Co_teaching project.
Ai-Learn
人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域
Awesome-Semi-Supervised-Semantic-Segmentation
A summary of recent semi-supervised semantic segmentation methods
break-the-ice-with-python
The repository is about 100+ python programming exercise problem discussed, explained, and solved in different ways
Coursera-ML-AndrewNg-Notes
吴恩达老师的机器学习课程个人笔记
CVPR2021-Papers-with-Code
CVPR 2021 论文和开源项目合集
data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
deep-learning-for-image-processing
deep learning for image processing including classification and object-detection etc.
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scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
gao-qing-shang
chat
Hello-world
Repository practice
leeml-notes
李宏毅《机器学习》笔记，在线阅读地址：https://datawhalechina.github.io/leeml-notes
LZU-Auto-COVID-Health-Report
LZU Auto COVID Health Report.(兰州大学疫情期间自动定时健康打卡)
nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
OrganSegRSTN_PyTorch
PyTorch implementation of OrganSegRSTN - CVPR 2018
Python-100-Days
Python - 100天从新手到大师
PyTorch-Tutorial
Build your neural network easy and fast, 莫烦Python中文教学
pytudes
Python programs, usually short, of considerable difficulty, to perfect particular skills.
Ref2Bib
给定一个参考文献列表，爬取谷歌学术生成bib文件
TorchSemiSeg
[CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
U2PL
[CVPR'22] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
understanding_dl
A lecture note for understanding deep learning
UniMatch
Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation