A curated list of Deep Learning, Reinforcement Learning, Machine Learning, Data Science, Recommendation, Chatbot
- Tutorial & Lecture
- 홍콩 과기대 김성훈 교수님의 모두의 딥러닝
- Deep Learning Tutorial from Tensorflow Blog
- Andrew Ng's Coursera Machine Learning
- Stanford - CS231n: Convolutional Neural Networks for Visual Recognition : [Video], [Korean], [Video - Korean]
- Stanford - CS224n: Deep Learning for Natural Language Processing : [Video]
- Stanford - Unsupervised Feature Learning and Deep Learning Tutorial
- Stanford - Tensorflow for Deep Learning Research
- MIT - 6.S191: Introduction to Deep Learning
- MIT - 6.S094: Deep Learning for Self-Driving Cars
- Oxford - Deep NLP 2017 course
- Deep learning courses at UC Berkeley
- T81-558:Applications of Deep Neural Networks
- MILA - DEEP LEARNING AND REINFORCEMENT LEARNING SUMMER SCHOOL 2017 : [Video]
- CS 598 LAZ: Cutting-Edge Trends in Deep Learning and Recognition
- KAIST Machine Learning Lecture
- Udacity - Deep Learning by Google
- Python Deep Learning with Keras - Machine Learning Mastery
- Practical Deep Learning For Coders—18 hours of lessons for free
- Deep Learning for Speech and Language
- 동국대 홍정모 교수님의 C++로 배우는 딥러닝
- Enjoy DL
- Laon People 머신러닝/딥러닝 블로그
- TensorFlow Slim 실습
- TensorFlow Workshop
- TensorFlow Tutorials
- TensorFlow Tutorial : [Video]
- Machine Learning & Deep Learning
- T아카데미 인공지능을 위한 머신러닝 알고리즘 강의
- Deep Learning course: lecture slides and lab notebooks - Master Datascience Paris Saclay
- Learning Tensorflow - Beginner-level tutorials for a powerful framework
- Tensorflow for Deep Learning : [Video]
- 텐서플로우 기초 이해하기
- Effective Tensorflow
- Introduction to Deep Neural Networks with Keras and Tensorflow
- PyTorch로 시작하는 딥러닝 입문 CAMP 1기 강의자료
- 패스트캠퍼스 Deep Learning 강의 자료
- 딥러닝 교육 자료
- Keras 레퍼런스 - CodeOnWeb
- DeepSchool.io - Deep Learning tutorials in jupyter notebooks
- Deep Learning Course - PyTorch
- TensorFlow Tutorial and Examples for Beginners with Latest APIs
- PyTorch Zero To All
- FastCampus Deep Learning NLP Chatbot
- 최신 논문으로 시작하는 딥러닝 - 최성준님 : [Code]
- Everybody Tensorflow
- 이찬우님의 패스트 캠퍼스 TensorFlow 딥러닝 강의자료
- 1. Machine Learning Basic, Linear Regression, Logistic Regression
- 2. Feed Forward Neural Network
- 3. Pipeline, TFRecord, Queue Runners, Dataset Framework
- 4. Convolutional Neural Network
- 5. Recurrent Neural Network
- 6. RNN Cells, Advanced RNNs
- 7. High Level APIs, Estimator, Experiment
- 8. Word2vec, GAN Basic
- Community
- TensorFlow KR Facebook Group
- AI Korea Facebook Group
- AI Korea
- AI Korea Reddit
- 텐서플로우 블로그
- Machine Learning Reddit
- Deep Learning Facebook Group
- Deep AI Facebook Group
- 모두의 연구소 커뮤니티 Facebook Group
- 모두의 연구소
- KERAS.AI Facebook Group
- Bigdata Machine Learning Facebook Group
- Big Data Korea Facebook Group
- 딥러닝 솔루션 그룹 Facebook Group
- AI DEV 인공지능 개발자 모임
- Distill - Machine Learning Research Journal
- ArxivSanityKr
- Towards Data Science - Sharing concepts, ideas, and codes.
- 카카오 AI 매거진
- HillClimber.ai - a curated machine learning mashup
- Article
- Andrej Karpathy's Deep Learning Blog
- 머신러닝 딥러닝 입문 시 도움 되는 강좌
- 딥러닝 입문자용 글 모음
- 딥러닝 공부 방법
- 딥러닝 공부를 처음 시작 하는 초심자가 꼭 공부 해야 하는 것이 아닌 것
- Practical seq2seq
- New York University Deep Learning Natural Language Processing Lecture Note
- Intro into Keras and Image Classification : [Video]
- The Black Magic of Deep Learning - Tips and Tricks for the practitioner
- How a Japanese cucumber farmer is using deep learning and TensorFlow
- [개앞맵시] 스카이넷도 딥러닝부터
- Keras 강좌
- Coding a Deep Neural Network to Steer a Car: Step By Step
- Torch와 OpenCV를 활용한 실시간 이미지 분류 데모
- Variational Autoencoders Explained
- Generative Adversarial Networks (GANs) in 50 lines of code (PyTorch)
- 이슈카님의 딥러닝 블로그 : CS231n
- Hama님의 딥러닝 블로그
- A Machine Learning Craftsmanship Blog
- DeepLAB - [머신러닝레볼루션] RNN과 LSTM - 쫄지말자 딥러닝
- DeepMind just published a mind blowing paper: PathNet
- Deep Learning for Noobs [Part 2] – Hacker Noon
- MNIST Generative Adversarial Model in Keras
- Image Recognition in Python with Keras
- 유재준님의 딥러닝 블로그
- Food Classification with Deep Learning in Keras / Tensorflow
- Accelerating Deep Learning with Multiprocess Image Augmentation in Keras
- Introduction to deep learning for machine vision tasks using Keras
- The AWS Deep Learning AMI, Now with Ubuntu
- Intel’s BigDL on Databricks Distributed deep learning on Apache Spark
- Deep Learning Research Review: Natural Language Processing
- Getting Started with Tensorflow
- 최근우님의 딥러닝 블로그
- 전상혁님의 머신러닝/딥러닝 블로그
- Gunho Choi님의 딥러닝 큐레이션 리스트
- nthought님의 딥러닝/데이터마이닝 블로그
- KH님의 딥러닝 블로그
- Deep Learning and Machine Learning Guide: Part I
- Deep Learning and Machine Learning Guide: Part II
- Deep Learning and Machine Learning Guide: Part III
- Deep Learning 학습 자료 정리
- Deep Learning with Keras
- Activation Function
- Deep Learning Conference 후기
- Building an Image Classification Web Application Using VGG-16
- PREPARING A LARGE-SCALE IMAGE DATASET WITH TENSORFLOW'S TFRECORD FILES
- Distributed Deep Learning with Apache Spark and Keras
- 내가 찾은 Deep Learning 공부 최단경로
- PyTorch MNIST Example
- CNN 역전파를 이해하는 가장 쉬운 방법
- Recurrent Neural Network(RNN)과 LSTM
- Data Science와 TensorFlow Study 정리 : Data Science와 TensorFlow Study Blog
- Learn TensorFlow and deep learning, without a Ph.D
- Visualizing parts of Convolutional Neural Networks using Keras and Cats
- Machine Learning is Fun!
- Machine Learning is Fun! The world’s easiest introduction to Machine Learning : [Korean]
- Machine Learning is Fun! Part 2 Using Machine Learning to generate Super Mario Maker levels : [Korean]
- Machine Learning is Fun! Part 3: Deep Learning and Convolutional Neural Networks : [Korean]
- Machine Learning is Fun! Part 4: Modern Face Recognition with Deep Learning : [Korean]
- Machine Learning is Fun Part 5: Language Translation with Deep Learning and the Magic of Sequences : [Korean]
- Machine Learning is Fun Part 6: How to do Speech Recognition with Deep Learning
- Machine Learning is Fun Part 7: Abusing Generative Adversarial Networks to Make 8-bit Pixel Art
- 딥러닝을 이용한 주가 예측
- 솔라리스의 인공지능 연구실
- Directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library
- Using Caffe with your own dataset
- Sang-Kil Park님의 딥러닝 블로그
- Image Classification and Segmentation with Tensorflow and TF-Slim
- Reuters-21578 text classification with Gensim and Keras
- How to Set Up a Deep Learning Environment on AWS with Keras/Thean
- Bumjun Kim님의 딥러닝 블로그
- Generative Adversarial Networks – Hot Topic in Machine Learning
- 조대협님의 머신러닝/딥러닝 블로그
- RNN(Recurrent Neural Network)과 Torch로 발라드곡 작사하기
- 모두의 딥러닝 강의 정리
- Arthur Juliani's Deep Learning Blog
- Tutorial: Optimizing Neural Networks using Keras (Image recognition)
- A curated list of resources related to NLP (Natural Language Processing) for Korean + NLP resources in Korean
- 딥러닝과 에스프레소북 그리고 이것저것들
- Adit Deshpande's Deep Learning Blos
- Keras Tutorial: The Ultimate Beginner's Guide to Deep Learning in Python
- LSTM(RNN) 소개
- 엑소사랑하자 - OpenFace로 우리 오빠들 얼굴 인식하기
- Deep Learning Papers Reading Roadmap
- [번역] A Beginner's Guide To Understanding Convolutional Neural Networks
- RNNS IN TENSORFLOW, A PRACTICAL GUIDE AND UNDOCUMENTED FEATURES
- Image Completion with Deep Learning in TensorFlow
- DeepLearning Ninja001 - Hello Tensorflow
- 딥러닝을 처음 시작하는 분들을 위해
- List of Pycon2016 session related with ML
- Awesome - Most Cited Deep Learning Papers
- 테리님의 딥러닝 블로그
- Machine Learning & Deep Learning Tutorials
- Deep Learning for Dummies, Carey Nachenberg
- TensorFlow-v1.0.0 + Keras 설치 (Windows/Linux/macOS)
- Deep Learning based Detection
- LSTM 과 ResNet
- TensorFlow: How to optimise your input pipeline with queues and multi-threading
- Image denoising with Autoencoder in Keras
- How to Build an Image Classification Web App With VGG-16
- Deep Learning Project Workflow
- [AI기획]경쟁 통해 배우는 인공지능 기술 GAN
- How these researchers tried something unconventional to come out with a smaller yet better Image Recognition
- Understanding Neural Networks Through Deep Visualization
- Picking an optimizer for Style Transfer
- Deep Learning with Keras on Google Compute Engine
- Clickbaits Revisited: Deep Learning on Title + Content Features to Tackle Clickbaits
- 텐서플로우 시작하기
- Baidu released PaddlePaddle Jupyter notebook
- ratsgo님의 블로그
- Faster R-CNN
- TensorFlow RNN Tutorial
- Build Your Own Text-to-Speech Applications with Amazon Polly
- Five video classification methods implemented in Keras and TensorFlow
- Build a talking, face-recognizing doorbell for about $100
- Deep Learning for Vision Guided Language And Image Generation
- 텐서보드 - TensorBoard 시작하기
- Classifying White Blood Cells With Deep Learning
- Diving Into Natural Language Processing
- Deep Learning with Emojis - not Math
- 겐[GANs]이 혁신할 인공지능 번역 기술
- 고려대학교 Deep Learning 세미나
- Awesome-Pytorch-list
- Artificial Intelligence GitBook
- Deploy Deep Learning Models on Amazon ECS
- DeepLAB : [논문반/논문세미나] SEGAN : Speech Enhancement Generative Adversarial Network
- awesome-deep-vision-web-demo
- Introducing tf-seq2seq: An Open Source Sequence-to-Sequence Framework in TensorFlow
- Kaggle DSTL Competition
- 14 DESIGN PATTERNS TO IMPROVE YOUR CONVOLUTIONAL NEURAL NETWORKS
- MXNet을 활용한 이미지 분류 앱 개발하기
- Tensorflow Tutorial 2: image classifier using convolutional neural network
- Rohan & Lenny #3: Recurrent Neural Networks & LSTMs
- Awesome-korean-nlp
- Deep learning for satellite imagery via image segmentation
- 지능형 한국어 형태소 분석기 - Korean Intelligent Word Identifier
- Transfer Learning using Keras
- Agustinus Kristiadi's Blog [GAN]
- Everything about Self Driving Cars Explained for Non-Engineers
- Kaggle Data Science Bown 2017 참가기[지능정보기술연구원]
- The GAN Zoo
- THE NEURAL NETWORK ZOO
- Classification datasets results
- Deeplunch팀의 Kaggle Data Science Bowl 도전기[1] - 케글 도전 팁
- A Brief History of CNNs in Image Segmentation: From R-CNN to Mask R-CNN
- Running BigDL, Deep Learning for Apache Spark, on AWS
- ImageNet: VGGNet, ResNet, Inception, and Xception with Keras
- TensorFlow: A proposal of good practices for files, folders and models architecture
- The Modern History of Object Recognition — Infographic
- Learning Deep Learning with Keras
- Deep Learning: Language identification using Keras & TensorFlow
- Deep Learning Papers by task
- Deep Learning Tutorials for 10 Weeks
- Keras Tutorial: Deep Learning in Python
- 2nd place solution for the 2017 national datascience bowl
- Deep learning for complete beginners: convolutional neural networks with keras
- Deep Learning으로 학습된 Object Detection Model 에 대해 정리한 Archive
- Face recognition with Keras and OpenCV
- Image segmentation with Neural Net
- GANs - Generative Adversarial Networks
- Neural networks for algorithmic trading 1.2 — Correct time series forecasting + backtesting
- 22 must watch talks on Python for Deep Learning, Machine Learning & Data Science - from PyData 2017, Amsterdam
- 라즈베리파이기반 TensorFlow 사물인식 로봇
- 라즈베리파이기반 YOLO 사물인식 로봇
- Deep Learning #3: More on CNNs & Handling Overfitting
- pyTorch Tutorials
- fast.ai: How I built a deep learning application to detect invasive species in just 1 day and for $12.60
- Picasso: A free open-source visualizer for Convolutional Neural Networks
- Using Machine Learning to Explore Neural Network Architecture
- Convolutional Methods for Text
- Applying deep learning to real-world problems
- Using TensorFlow to build image-to-text application
- Your tl;dr by an ai: a deep reinforced model for abstractive summarization
- Practical UseCases of Deep Learning Techniques… Part II
- Caption this, with TensorFlow
- Image Segmentation using deconvolution layer in Tensorflow
- Exploring LSTMs
- [YOLO DARKNET] 구성 및 설치, 사용방법
- You can probably use deep learning even if your data isn't that big
- TensorFlow for Hackers
- TensorFlow Basics — TensorFlow for Hackers Part I
- Building a Simple Neural Network — TensorFlow for Hackers Part II
- Building a Cat Detector using Convolutional Neural Networks — TensorFlow for Hackers Part III
- Neural Network from Scratch — TensorFlow for Hackers Part IV
- Making a Predictive Keyboard using Recurrent Neural Networks — TensorFlow for Hackers Part V
- Human Activity Recognition using LSTMs on Android — TensorFlow for Hackers Part VI
- Visualizing TensorFlow Graphs in Jupyter Notebooks
- Safe Crime Prediction
- A neural approach to relational reasoning
- Neural Translation of Musical Style
- RNN을 이용한 한글 자동 띄어쓰기
- Object detection with neural networks — a simple tutorial using keras
- GAN by Example using Keras on Tensorflow Backend
- Supercharge your Computer Vision models with the TensorFlow Object Detection API
- Stacking Made Easy: An Introduction to StackNet by Competitions Grandmaster Marios Michailidis - KazAnova
- Generative Adversarial Networks for Beginners
- Accelerating Deep Learning Research with the Tensor2Tensor Library
- Building a Real-Time Object Recognition App with Tensorflow and OpenCV
- How HBO’s Silicon Valley built “Not Hotdog” with mobile TensorFlow, Keras & React Native
- How to Visualize Your Recurrent Neural Network with Attention in Keras
- Interpreting neurons in an LSTM network
- 머신러닝 실습 with Tensorflow
- Pytorch를 사용한 단 50줄로 코드로 짜보는 GAN
- DeepMind’s Relational Reasoning Networks — Demystified
- Artificial Inteligence
- How to deploy Machine Learning models with TensorFlow. Part 2— containerize it!
- Predicting the Success of a Reddit Submission with Deep Learning and Keras
- CycleGAN : Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks - 컨셉
- Find Distinct People in a Video with Amazon Rekognition
- TensorFlow Neural Machine Translation Tutorial
- Galaxy Zoo classification with Keras
- 김태희의 닮은 꼴도 머신러닝으로 구분할 수 있을까?
- An end to end implementation of a Machine Learning pipeline
- Debugging & Visualising training of Neural Network with TensorBoard
- Deploy Tensorflow Docker Image to AWS ECS
- Perform sentiment analysis with LSTMs, using TensorFlow
- Textboxes - 2016 : Image Text Detection 논문 리뷰
- 37 Reasons why your Neural Network is not working
- 37 Reasons why your Neural Network is not working 번역
- A Step-by-Step Guide to Synthesizing Adversarial Examples
- Deep Learning for NLP Best Practices
- Exploiting the Unique Features of the Apache MXNet Deep Learning Framework with a Cheat Sheet
- How to train your own Object Detector with TensorFlow’s Object Detector API
- Classifying traffic signs with Apache MXNet: An introduction to computer vision with neural networks
- Towards Next Generation Deep Learning Framework - An Introduction to MXNet/Gluon
- A gentle introduction to Doc2Vec
- A non-NLP application of Word2Vec
- Deep Learning #4: Why You Need to Start Using Embedding Layers
- Apache MXNet에 대한 모든 것!
- MXNet 기반 추천 오픈 소스 딥러닝 프로젝트 모음
- 클라우드에 딱 맞는 MXNet의 5가지 딥러닝 학습 기능
- Applying Deep Learning to Time Series Forecasting with TensorFlow
- Classifying e-commerce products based on images and text
- Autoencoders — Bits and Bytes of Deep Learning
- TensorFlow Photo x-Ray Object Detection with App Engine
- Seq2Seq - ICML17 Tutorial
- Jamie Kang님의 머신러닝 블로그
- Seamlessly Scale Predictions with AWS Lambda and MXNet
- Deep Learning on AWS Batch
- Twitter Sentiment Analysis with Gensim Word2Vec and Keras Convolutional Networks
- Using AI to Super Compress Images
- Where’s Waldo : Terminator Edition
- Vanishing Gradient Problem
- Estimating the Location of Images Using MXNet and Multimedia Commons Dataset on AWS EC2
- Captioning Novel Objects in Images
- Training MXNet
- Image Augmentation for Deep Learning using Keras and Histogram Equalization
- Learn.AI님의 GAN 정리
- 옹쿠님의 Deep Learning 블로그
- Getting Up and Running with PyTorch on Amazon Cloud
- Credit Card Fraud Detection using Autoencoders in Keras — TensorFlow for Hackers Part VII
- Building a Facial Recognition Pipeline with Deep Learning in Tensorflow
- Generative Adversarial Networks [GANs]: Engine and Applications
- Machine Learning for Humans
- 이찬우님의 Deep Learning Blog
- [Lecture] How to build a recognition system - Part 1: best practices
- [Lecture] Evolution: from vanilla RNN to GRU & LSTMs
- Connecting the dots for a Deep Learning App
- An Intuitive Guide to Deep Network Architectures
- Secret Sauce behind the beauty of Deep Learning: Beginners guide to Activation Functions
- Tensorflow Object Detection API Tutorial
- A Deep Learning Based AI for Path of Exile: A Series
- Deploying your Keras model using Keras.JS
- Learning GAN
- A Word2Vec Keras tutorial
- Neural Networks Part 2: Implementing a Neural Network function in python using Keras
- Tutorial - What is a variational autoencoder?
- 2017 beginner's review of GAN architectures
- My Neural Network isn't working! What should I do?
- Keras shoot-out: TensorFlow vs MXNet
- Applied Deep Learning
- BigData와 결합한, 분산 Deep Learning 그 의미와 접근 방법에 대하여
- Deep Learning with Intel’s BigDL and Apache Spark
- My Workflow of Supervised Learning - 지도학습의 자세한 나만의 워크플로우
- Python gensim Word2Vec tutorial with TensorFlow and Keras
- Time Series Prediction Using Recurrent Neural Networks [LSTMs]
- GCP ML 엔진 튜토리얼: 텐서플로우 고수준 API로 작성된 CIFAR-10 모델의 초모수 최적화 하기
- Familiarization of Sequence to Sequence model in Deep Learning
- Understanding LSTM in Tensorflow[MNIST dataset]
- Deep Learning for Object Detection: A Comprehensive Review
- Detecting Malicious Requests with Keras & Tensorflow
- Recognizing Game Genres From Screenshots using CNNs
- Deep Learning with Intel’s BigDL and Apache Spark
- Keras Tutorial: Content Based Image Retrieval Using a Convolutional Denoising Autoencoder
- How to write distributed TensorFlow code — with an example on TensorPort
- Build your own Machine Learning Visualizations with the new TensorBoard API
- Gradient Trader Part 1: The Surprising Usefulness of Autoencoders
- Create self-driving trucks inside Euro Truck Simulator 2
- Dealing with Unbalanced Classes in Machine Learning
- Introduction to TensorFlow Datasets and Estimators
- Higher-Level APIs in TensorFlow
- Building a Toy Detector with Tensorflow Object Detection API
- 딥러닝 기반 자연어처리 기법의 최근 연구 동향
- Recurrent Neural Network [RNN] 이해하기
- Wasserstein GAN in Keras
- PyTorch tutorial distilled
- Tensorpack과 Multigpu를 활용한 빠른 트레이닝 코드 작성하기
- ‘Image Classification’ Outline
- A ten-minute introduction to sequence-to-sequence learning in Keras
- A new kind of pooling layer for faster and sharper convergence
- Understanding emotions — from Keras to pyTorch
- TensorFlow Datasets 및 Estimators를 소개합니다.
- Visualizing your model using TensorBoard
- Towards data set augmentation with GANs
- TensorFlow in a Nutshell
- Introducing NNVM Compiler: A New Open End-to-End Compiler for AI Frameworks
- Vanilla LSTM with numpy
- Sentiment analysis with Apache MXNet
- Question answering with TensorFlow
- Recurrent neural networks and LSTM Tutorial in Python and TensorFlow
- Serving PyTorch Models on AWS Lambda with Caffe2 & ONNX
- Behind the Magic: How we built the ARKit Sudoku Solver
- TensorFlow Lattice: Flexibility Empowered by Prior Knowledge
- 딥러닝과 OpenCV를 활용해 사진 속 글자 검출하기
- 옥수별님의 머신러닝/딥러닝 블로그
- Neural Networks for Advertisers
- Recurrent Neural Networks for Email List Churn Prediction
- Tensorflow Text Classification – Python Deep Learning
- D.Voice: 딥러닝 음성 합성 엔진
- Video Analysis to Detect Suspicious Activity Based on Deep Learning
- Building a Translation System In Minutes
- Google and Uber’s Best Practices for Deep Learning
- Introducing Gluon — An Easy-to-Use Programming Interface for Flexible Deep Learning : [한글]
- Gender Distribution in North Korean Posters
- Attention in Neural Networks and How to Use It
- TF-Slim 시작하기
- Improving Real-Time Object Detection with YOLO
- How to unit test machine learning code
- Batch normalization in Neural Networks
- Dog Breed Classification using Deep Learning: hands-on approach
- 레진 데이터 챌린지 2017
- Distributed training in the cloud: Cloud Machine Learning Engine
- Object detection with TensorFlow
- Simple MNIST Autoencoder in TensorFlow
- What is a CapsNet or Capsule Network?
- Latest Deep Learning OCR with Keras and Supervisely in 15 minutes
- Machine Learning Meets Fashion
- [카카오AI리포트]딥러닝과 데이터
- CapsuleNet on MNIST
- How do CNNs Deal with Position Differences? : [번역]
- Slide
- Deep Learning 101: Slides
- Layer Normalization
- TensorFlow Dev Summit 2017 요약
- Google Dev Summit Extended Seoul - TensorFlow: Tensorboard & Keras
- 2017 tensor flow dev summit
- CNN 초보자가 만드는 초보자 가이드 (VGG 약간 포함)
- TensorFlow Tutorial
- Knowing when to look : Adaptive Attention via A Visual Sentinel for Image Captioning
- 기계 학습의 현재와 미래
- Amazon 인공 지능(AI) 서비스 및 AWS 기반 딥러닝 활용 방법
- 지적 대화를 위한 깊고 넓은 딥러닝 PyCon APAC 2016 : [Video]
- 딥러닝(Deep Learning) using DeepDetect
- Explaining and harnessing adversarial examples (2015)
- Paper Reading : Learning from simulated and unsupervised images through adversarial training
- One-Shot Learning
- A Gentle Autoencoder Tutorial (with keras) : [Code]
- Toward Best Practices of TensorFlow Code Patterns
- Generative adversarial networks
- AI 그까이거
- 인공지능: 변화와 능력개발
- 인공지능, 기계학습 그리고 딥러닝
- Deep Learning Into Advance - 1. Image, ConvNet
- 텐서플로 걸음마 (TensorFlow Tutorial)
- Convolutional neural network in practice
- 쫄지말자딥러닝2 - CNN RNN 포함버전
- Introduction to Deep Learning with TensorFlow
- 딥러닝을 이용한 자연어처리의 연구동향
- 기계학습 / 딥러닝이란 무엇인가
- Spark machine learning & deep learning
- 의료빅데이터 컨테스트 결과 보고서
- Deep learning
- Squeezing Deep Learning Into Mobile Phones
- Image Segmentation
- Understanding deep learning requires rethinking generalization 2017 1/2
- Understanding deep learning requires rethinking generalization 2017 2/2
- Visualizing data using t-SNE
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- Movix.ai — movie recommendations with Deep Learning
- Data Piques's Recommendation Article
- Intro to Recommender Systems: Collaborative Filtering
- Explicit Matrix Factorization: ALS, SGD, and All That Jazz
- Intro to Implicit Matrix Factorization: Classic ALS with Sketchfab Models
- Embedding Everything for Anything2Anything Recommendations
- Learning to Rank Sketchfab Models with LightFM
- Using Keras' Pretrained Neural Networks for Visual Similarity Recommendations
- Matrix Factorization in PyTorch
- AWS re:Invent 2016: Using MXNet for Recommendation Modeling at Scale (MAC306)
- LibRec - A Leading Java Library for Recommender Systems
- Github-recommendation-system-using-word2vec
- Kaggle_Santander-Product-Recommendation
- Kaggle_Expedia-hotel-recommendations
- Recommender Systems - Coursera Machine Learning 강의 노트
- From Labelling Open data images to building a private recommender system
- Applying Deep Learning to Collaborative Filtering: How Hulu builds its industry leading
- Deep Learning with Tensorflow - Recommendation System with a Restrictive Boltzmann Machine
- Alexandros Karatzoglou: Deep Learning for Recommender Systems : [Slide]
- Factorization Machines for Recommendation Systems
- Understanding matrix factorization for recommendation
- Matrix Factorization with Tensorflow
- Exploring Recommender Systems
- TensorFlow implementation of an arbitrary order Factorization Machine
- How to build a movie recommender with GRAKN.AI
- Evaluating Recommender Systems
- What you wanted to know about Mean Average Precision
- Evaluating recommender systems
- Discounted Cumulative Gain
- 평가가 중요하다
- Evaluating Recommender Systems - Explaining F-Score, Recall and Precision using Real Data Set from Apontador
- Evaluation - python-recsys
- HT2014 Tutorial: Evaluating Recommender Systems - Ensuring Replicability of Evaluation
- How Recommendation Systems Work On Amazon & Netflix - Simplilearn Webinar
- Deep Learning for Personalized Search and Recommender Systems
- Finding similar images using autoencoders
- Intro to Machine Learning - Building a Recommendation Model using Keras
- Recommender systems with TensorFlow - Google I/O Extended Bangkok 2017 : [Code]
- SVD Recommendations using Tensorflow
- Deep-Learning-for-Recommendation-Systems
- Genre Essentials — Building an Album Recommender System
- How Deep Neural Networks for YouTube Recommendations Work
- Deep neural networks for YouTube recommendations
- Curated list of Recommendation System
- A Glimpse into Deep Learning for Recommender Systems
- Deep Learning for Recommender Systems RecSys2017 Tutorial
- Code for our ACM RecSys 2017 paper "Personalizing Session-based Recommendation with Hierarchical Recurrent Neural Networks"
- Recommender Systems In Industry
- Deep AutoEncoders for Collaborative Filtering
- Deep NLP-based Recommenders at Finn.no
- Film recommendation engine - Kaggle
- Public Recommendation Data - goodbooks-10k
- Deep Learning in Recommender Systems - RecSys Summer School 2017
- How Did We Build Book Recommender Systems in an Hour Part 1 — The Fundamentals
- How Did We Build Book Recommender Systems in An Hour Part 2 — k Nearest Neighbors and Matrix Factorization
- Binary Representations in Recommendations
- Music Recommendations with Collaborative Filtering and Cosine Distance
- Matrix Factorization for Movie Recommendations in Python
- Naver 추쳔 관련 블로그
- Building Recommender System for GitHub
- RecSys 2017 Summary
- A Cost-Effective and Scalable Collaborative Filtering based Recommender System
- A news recommendation engine driven by collaborative reader behavior
- Spotify’s Discover Weekly: How machine learning finds your new music
- Approximate Nearest Neighbours for Recommender Systems
- Deep matrix factorization using Apache MXNet
- LastFM Artist Recommender
- 인공지능 추천 시스템 AiRS 개발기 : 모델링과 시스템
- 맥주마시며 만들어본 딥러닝 맥주 추천엔진
- Building a Real-time Recommendation Engine With Neo4j - William Lyon - OSCON 2017
- Evaluation in IR system [검색 시스템의 평가]
- Precision, Recall, AP[Average Precision], MAP[Mean Average Precision]
- Unranked Retrieval Evaluation
- accuracy, precision, recall의 차이
- 세계 챗봇 생태계 분석
- 챗봇의 구조: 챗봇은 AI가 필요한가?
- Building AI Chat bot using Python 3 & TensorFlow
- Developing Korean Chatbot 101
- 20170227 파이썬으로 챗봇_만들기
- AWS - Building Better Bots
- Integrate Your Amazon Lex Bot with Any Messaging Service
- Let Android dream electric sheep: Making emotion model for chat-bot with Python3, NLTK and TensorFlow
- Python과 Tensorflow를 활용한 AI Chatbot 개발 및 실무 적용