Meachine Learning

Regression

• Linear Regression(http://localhost:8888/notebooks/study/regression/LinearRegression.ipynb)

• Logistic Regression(http://localhost:8888/notebooks/study/regression/LogisticRegression.ipynb)

Classification

• Softmax Classification(http://localhost:8888/notebooks/study/classification/Softmax_classification.ipynb)
• SVM(http://localhost:8888/notebooks/classification/svm/svm.ipynb)
• Decision Tree(http://localhost:8888/notebooks/classification/decision_tree/Decision%20Tree.ipynb)

Clustering

• KMeans (http://localhost:8888/notebooks/clustering/KMeans.ipynb)

Dimensionality Reduction

Neural Network

BackPropagation

ReLU

Dropout

Convolutional Neural Networks

Recurrent Neural Network

Deep Learning

DBN

DQN

GAN

Tutor

ML tutorials

• 모두를 위한 머신러닝(https://hunkim.github.io/ml/)
• Coursera Andrew Ng (https://class.coursera.org/ml-003/lecture)
• http://www.holehouse.org/mlclass/
• StanFord tutorial http://deeplearning.stanford.edu/tutorial/

Lecture Videos

• CS231n: Convolutional Neural Networks for Visual Recognition http://cs231n.stanford.edu/syllabus.html
• CS224d: Deep Learning for Natural Language Processing http://cs224d.stanford.edu/syllabus.html

Tensorflow

• Official site https://www.,tensorflow.org
• Simple Tutorials https://github.com/nlintz/TensorFlow-Tutorials
• Another TensorFlow Tutorials https://github.com/pkmital/tensorflow_tutorials
• TensorFlow Examples https://github.com/aymericdamien/TensorFlow-Examples
• Deep Learning @Udacity https://www.udacity.com/course/viewer#!/c-ud730/l-6370362152/m-6379811817
• https://github.com/hunkim/DeepLearningZeroToAll

Article or Paper

https://github.com/hunkim/DeepLearningZeroToAll

Stanford TensorFlow

http://web.stanford.edu/class/cs20si/syllabus.html

cs224d

cs231n

EnjoyDL

https://www.facebook.com/enjoyhavefun/

Tutorial

https://github.com/aymericdamien/TensorFlow-Examples https://github.com/nlintz/TensorFlow-Tutorials

Paper

https://github.com/nyu-dl/NLP_DL_Lecture_Note/blob/master/lecture_note.pdf

Article

backprop

https://medium.com/@karpathy/yes-you-should-understand-backprop-e2f06eab496b#.ggjyiwhyg

PG DQN

https://arxiv.org/abs/1702.06230

DOOM

https://arxiv.org/pdf/1611.01779.pdf

Chiness chess

https://github.com/jireh-father/irelia

Tensorboard in jupyter

http://stackoverflow.com/questions/38189119/simple-way-to-visualize-a-tensorflow-graph-in-jupyter

slideshare

조형주 님 - High level-api in tensorflow https://www.slideshare.net/Hyun…/high-levelapi-in-tensorflow 이태영 님 - Sequence Models and the RNN API Produced https://www.slideshare.net/taey…/2017-tensor-flow-dev-summit 전태균 님 - TensorFlow: Tensorboard & Keras https://www.slideshare.net/…/google-dev-summit-extended-seo… 김진중 님 - TensorFlow Dev Summit 2017 요약 https://www.slideshare.net/hacke…/tensorflow-dev-summit-2017

book

TensorFlow For Machine Intelligence: A hands-on introduction to learning algorithms Kindle Edition by Sam Abrahams (Author), Danijar Hafner (Author), Erik Erwitt (Author), Ariel Scarpinelli (Author), etc.

github

chatbot

jin kim(golbin)

seq2seq

http://suriyadeepan.github.io/2016-12-31-practical-seq2seq/