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100-days-of-ml-code

100 Days of ML Coding

aind2-cnn

AIND Term 2 -- Lesson on Convolutional Neural Networks

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

awesome-machine-learning-interpretability

A curated list of awesome machine learning interpretability resources.

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

bayesianoptimization

A Python implementation of global optimization with gaussian processes.

best-subset

Comparisons between best subset selection and other popular estimators for sparse regression

bitcoin-whitepaper-chinese-translation

cnn-text-classification-tf

Convolutional Neural Network for Text Classification in Tensorflow

cnn_sentence

My version of CNNs for sentence classification

deep-learning-interview-book

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

deepbayes-2018

Seminars DeepBayes Summer School 2018

deeplearningtutorials

Deep Learning与PyTorch入门实战视频教程

dlbook_notation

LaTeX files for the Deep Learning book notation

eat_tensorflow2_in_30_days

Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

edward

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

fonduer

:newspaper: a knowledge base construction engine for richly formatted data

functionality-scenario-test-a-2018

This repo. is functionality scenario test "Task A" for building AI Infrastructure, including train.py, pretrain model and image samples.

hangzhou_house_knowledge

2017年买房经历总结出来的买房购房知识分享给大家，希望对大家有所帮助。买房不易，且买且珍惜。Sharing the knowledge of buy an own house that according to the experience at hangzhou in 2017 to all the people. It's not easy to buy a own house, so I hope that it would be useful to everyone.

hyperparameter-optimization

Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms

ilearndeeplearning.py

This repository contains small projects related to Neural Networks and Deep Learning in general. Subject are closely linekd with articles I publish on Medium. I encourage you both to read as well as to check how the code works in the action.

interpretable_machine_learning_with_python

Practical techniques for training interpretable ML models, explaining ML models, and debugging ML models.

interview-notebook

:memo: 准备秋招学习笔记

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]

lihang-code

《统计学习方法》的代码实现

machine-learning-code-writing

Mathematical derivation and pure Python code implementation of machine learning algorithms.

machine-learning-notes

周志华《机器学习》手推笔记

ml-tutorial-experiment

Coding the Machine Learning Tutorial for Learning to Learn

mlss2018-madrid-gan

MLSS 2018 Madrid lecture materials on Generative Adversarial Networks (GANs)

models

Models and examples built with TensorFlow