Pinned Repositories
100-Days-Of-ML-Code
100 Days of ML Coding
2016-10-facebook-fact-check
Data and analysis for the BuzzFeed News article, "Hyperpartisan Facebook Pages Are Publishing False And Misleading Information At An Alarming Rate."
awesome-algorithm
Leetcode 题解 (跟随思路一步一步撸出代码) 及经典算法实现
Awesome-pytorch-list
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
awesome_deep_learning_interpretability
深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)
BayesByHypernet
Code for the paper Implicit Weight Uncertainty in Neural Networks
bayesian-machine-learning
Notebooks related to Bayesian methods for machine learning
Bayesian-Neural-Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace and more
deep-Bayesian-nonparametrics-papers
The collection of papers about combining deep learning and Bayesian nonparametrics
deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
zhong2024's Repositories
zhong2024/deep-Bayesian-nonparametrics-papers
The collection of papers about combining deep learning and Bayesian nonparametrics
zhong2024/deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
zhong2024/100-Days-Of-ML-Code
100 Days of ML Coding
zhong2024/awesome-algorithm
Leetcode 题解 (跟随思路一步一步撸出代码) 及经典算法实现
zhong2024/Awesome-pytorch-list
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
zhong2024/awesome_deep_learning_interpretability
深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)
zhong2024/bayesian-machine-learning
Notebooks related to Bayesian methods for machine learning
zhong2024/Bayesian-Neural-Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace and more
zhong2024/BayesianNeuralNetwork
a repo sharing Bayesian Neural Network recent papers
zhong2024/d2l-pytorch
This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.
zhong2024/Deep-Neural-Networks-HealthCare
Tangible and Practical Deep Learning Projects Repository for Healthcare such as Cancer, Drug Discovery, Genomic and More
zhong2024/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15个章节，近20万字。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
zhong2024/deeplearning-models
A collection of various deep learning architectures, models, and tips
zhong2024/Dive-into-DL-PyTorch
本项目将《动手学深度学习》（Dive into Deep Learning）原书中的MXNet代码实现改为PyTorch实现。
zhong2024/docs
TensorFlow documentation
zhong2024/edward
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
zhong2024/ESL-CN
The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。
zhong2024/learn-python3
Learn Python 3 Sample Code
zhong2024/Learning-from-data
记录Learning from data一书中的习题解答
zhong2024/MCDO
A pytorch implementation of MCDO(Monte-Carlo Dropout methods)
zhong2024/mlss2019-bayesian-deep-learning
MLSS2019 Tutorial on Bayesian Deep Learning
zhong2024/mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
zhong2024/numpy-ml
Machine learning, in numpy
zhong2024/planets1010
practising Git
zhong2024/PRML
PRML algorithms implemented in Python
zhong2024/Python
All Algorithms implemented in Python
zhong2024/pytorch-handbook
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
zhong2024/Reinforcement_learning_tutorial_with_demo
Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..
zhong2024/test1
test1 for Git
zhong2024/weight_uncertainty
Implementing Bayes by Backprop