- Korean translation of the Keras documentation
- Keras와 함께 딥러닝 백지부터 GANs까지! twitter login
- Getting to Know Keras for New Data Scientists
- Keras: Deep Learning library for Theano and TensorFlow
- Keras Cheat Sheet: Neural Networks in Python
- Deep Learning Cheat Sheet (using Python Libraries) - Data Science Central
- Keras로 Multi Layer Percentron 구현하기
- Keras_MNIST_Example.ipynb
- github.com/jaeho-kang/deep-learning/keras
- Easy-deep-learning-with-Keras 주로 텍스트 분석
- Keras로 대용량 이미지 처리하기
- keras-rl - Deep Reinforcement Learning for Keras. http://keras-rl.readthedocs.io
- Pre-trained DL Model for Keras
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- A ten-minute introduction to sequence-to-sequence learning in Keras
- Sequence to Sequence Learning with Keras
- seq2seq - A general-purpose encoder-decoder framework for Tensorflow
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- 케라스를 이용해 seq2seq를 10분안에 알려주기
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- Seq2seq Chatbot for Keras
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- How-To: Multi-GPU training with Keras, Python, and deep learning
- keras에서 GPU 사용하기
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- Why is Keras Running So Slow?
- Elephas: Distributed Deep Learning with Keras & Spark
- kapre - Keras Audio Preprocessors
- Keras++
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- jacobgil/dcgan.py
- keras-tqdm - Keras integration with TQDM progress bars
- Keras Adversarial Models
- Minimal Monte Carlo Policy Gradient (REINFORCE) Algorithm Implementation in Keras
- 케라스 레퍼런스
- github.com/jskDr/jamespy_py3
- One Shot Learning with Siamese Networks in Keras!
- Deep Learning with Emojis (not Math)
- Keras + Theano 시도: 3. 이미지 준비
- simple_rnn_encoder_decoder.py
- Integrating Keras & TensorFlow: The Keras workflow, expanded (TensorFlow Dev Summit 2017)
- Learning Deep Learning with Keras
- Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
- How to Set Up a Deep Learning Environment on AWS with Keras/Theano
- Abstract is out; Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras
- 가변 길이 입력 시퀀스에 대한 데이터 준비
- Random Effects Neural Networks in Edward and Keras
- Keras Visualization Toolkit
- 파이썬 코딩으로 말하는 데이터 분석 - 10. DTW (Data time wrapping)
- Neural Image Captioning (NIC) - Neural image captioning implementation with Keras based on Show and Tell
- Neural image captioning (NIC) implementation with Keras 2
- Predicting the Success of a Reddit Submission with Deep Learning and Keras
- Image Augmentation for Deep Learning using Keras and Histogram Equalization
- tykimos.github.io/Keras/category
- 케라스와 텐서플로우와의 통합
- 케라스 강좌 내용
- 학습 조기종료 시키기
- 학습과정 표시하기 (텐서보드 포함)
- 딥브릭(DeepBrick) 이야기
- 수치예측 모델 레시피
- 수치입력 수치예측 모델 레시피
- 수치입력 이진분류 모델 레시피
- 수치입력 다중클래스분류 모델 레시피
- 영상입력 수치예측 모델 레시피
- 영상입력 이진분류 모델 레시피
- 영상입력 다중클래스분류 모델 레시피
- 시계열수치입력 수치예측 모델 레시피
- 문장(시계열수치)입력 이진분류 모델 레시피
- 문장(시계열수치)입력 다중클래스분류 모델 레시피
- 하용호님의 '네 뇌에 딥러닝 인스톨' + 딥브릭 + 실습
- 클래스별로 학습과정 살펴보기
- 새로운 딥러닝 프레임웍 : Keras
- Keras 실습 01
- Keras 실습 02
- Keras 실습 03 - 1
- Deploying your Keras model using Keras.JS
- Betting system prediction using Deep Learning in python Keras
- Keras shoot-out: TensorFlow vs MXNet
- Apache MXNet support in Keras
- Search for the fastest Deep Learning Framework supported by Keras
- U-net on Keras 2.0
- Gender Distribution in North Korean Posters
- How to Use the Keras Functional API for Deep Learning
- Deep Learning과 Keras 기초 - 아샬(@ahastudio)
- Segmentation using Unet open version 학습 중간에 mask를 시각적으로 확인
- Deep Residual Unet (ResUNet) Segmentation in Keras TensorFlow
- Unet Segmentation in Keras TensorFlow
- Use Pretrained Model in Keras with Statoil dataset
- transfer learning을 이용한 feature extraction. LDA와 같은 지도학습을 사용하여 feature를 뽑아내는 것과 같은 방식
- Keras: Feature extraction on large datasets with Deep Learning
- Making AI Art with Style Transfer using Keras
- Neural Style Transfer-TF&Keras (2019/05/20)
- Intro into Image classification using Keras
- Building powerful image classification models using very little data
- Image Classification on Android using a Keras Model Deployed in Flask
- Building an Image Classifier Using Tensorflow Keras
- Galaxy Zoo classification with Keras
- Video classification with Keras and Deep Learning
- Spam Classification with Tensorflow-Keras
- Use Keras Deep Learning Models with Scikit-Learn in Python
- kerasapp - 코딩셰프의 3분 딥러닝, 케라스맛
- 케라스 맛보기
- Turning Design Mockups Into Code With Deep Learning
- Computer Vision Basics with Python Keras and OpenCV
- Understanding Dynamic Routing between Capsules (Capsule Networks)
- Predicting Fraud with Autoencoders and Keras
- How to build your own AlphaZero AI using Python and Keras
- AlphaZero가 AI에서 중요한 두가지 이유
- Alphago Zero방법론 복제를 통한 게임 Connect4를 플레이 구축
- 다른 게임을 플러그인하기 위해 코드를 적용하는 방법
- Python/Keras implementation of integrated gradients presented in "Axiomatic Attribution for Deep Networks" for explaining any model defined in Keras framework
- Hallucinogenic Deep Reinforcement Learning Using Python and Keras
- Using Keras via Docker
- Simple guide on how to generate ROC plot for Keras classifier
- Keras shoot-out: TensorFlow vs MXNet
- Deep Learning과 Keras 기초 - 아샬(@ahastudio)
- 세종국책연구단지에 딥러닝 모델 심기
- Keras와 HDF5으로 대용량 데이터 학습하기
- Keras gets a lightning fast backend!
- Keras implementation of Image OutPainting
- Google Colaboratory에서 Keras의 백엔드로서 MXNet을 설정하는 방법
- Keras on TPUs in Colab
- Predict Shakespeare with Cloud TPUs and Keras colab에서 TPU 사용
- tf.data examples for keras and estimator models
- 딥러닝의 Hello World, Fashion-MNIST
- Elmo Embeddings in Keras with TensorFlow hub
- Keras implementation of Deeplabv3+
- Deploying a Keras Deep Learning Model as a Web Application in Python flask 사용
- Review 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
- Standardizing on Keras: Guidance on High-level APIs in TensorFlow 2.0
- TensorFlow 2.0 + Keras Crash Course.ipynb
- Code for plotting the keras model graph
- tf.keras
- tf.keras for Researchers: Crash Course.ipynb
- 이미지만으로 내 중고물품의 카테고리를 자동으로 분류해준다면? (feat. Keras)
- 내 중고물품을 분류 해주는 모델 서빙하기(feat. Keras & Flask)
- Saving & Loading Keras Models
- Data Loader with tf.keras.utils.Sequence and datatable
- Using deep learning to “read your thoughts” — with Keras and EEG
- 리뷰에는 이미 별점이 있는데 별점을 또 예측해서 뭘 하나요
- A detailed example of how to use data generators with Keras
- How to Handle Missing Timesteps in Sequence Prediction Problems with Python
- Inside TensorFlow: tf.Keras (part 1)
- Inside TensorFlow: tf.Keras (part 2)
- Keras, 케라스 인공지능의 표준어
- Log melspectrogram layer using tensorflow.keras
- Welcome to Keras
- Shooting Hoops with Keras and TensorFlow || Zack Akil
- Fire and smoke detection with Keras and Deep Learning
- DACON 14회 금융문자분석 경진대회 59위
- Keras를 이용한 딥러닝 시작, ANN DNN, 손글씨 인식시키기 머신러닝 with Python - YouTube
- Practical Keras. Simple regression for the Numerai… | by Keno Leon | Medium
- keras Conv2D | Pega Devlog
- keras BatchNormalization | Pega Devlog
- 케라스 API를 사용한 사용자 정의 모델 만들기 with 텐서플로 2.3+2.4 Colaboratory
- 딥러닝 으로 리뷰에서 제품 속성 정보 추출하기 – 화해 블로그 | 기술 블로그
- Train a Vision Transformer on small datasets
- A Deep Dive into Transformers with TensorFlow and Keras: Part 1 - PyImageSearch
- Your First Deep Learning Project in Python with Keras Step-By-Step
- keras의 timeseries_dataset_from_array 사용시 주의할 점 – Passion is like genius; a miracle.
- Can not serialize… get_config() during keras model save and load and a loss func wrapper to ignore NaN in y_true – Passion is like genius; a miracle.
- Positional encoding for timeseries data – Passion is like genius; a miracle
- Park Chansung - Keras + Keras Kinetic + TPU 조합으로 손쉽게 Diffusion 학습 | Facebook
- Google Cloud에서 제공되는 TPU/GPU를 별도 인스턴스 프로비저닝 없이 Keras 코드에 활용. Keras Kinetic 유틸리티 라이브러리로 Diffusion 모델 간편 학습
- 더북(TheBook): 케라스 창시자에게 배우는 딥러닝 1~3장만
- 미분 가능 프로그래밍 (Differentiable Programming) - Google Docs
- keras-idiomatic-programmer - Handbooks and Code Samples for Software Engineers wanting to learn the Keras Machine Learning framework
- How convolutional neural networks see the world
- Understanding deep Convolutional Neural Networks with a practical use-case in Tensorflow and Keras
- Notes on my paper; On the Robustness of Deep Convolutional Neural Networks for Music Classification
- Fine-tuning Convolutional Neural Network on own data using Keras Tensorflow
- Introduction to 1D Convolutional Neural Networks in Keras for Time Sequences
- [Applying your Convolutional Neural Network: On-Demand Webinar and FAQ Now Available!
- Deep Learning Fundamental Series - Part 3
- MNIST Classification using CNN in Keras TensorFlow
- Keras에서 CNN학습 시키기
- 컨볼루션 신경망 모델을 위한 데이터 부풀리기
- Building a Convolutional Neural Network (CNN) in Keras
- Real-World Python Neural Nets Tutorial (Image Classification w/ CNN) | Tensorflow & Keras
- Step by step VGG16 implementation in Keras for beginners | by Rohit Thakur | Towards Data Science
- 딥러닝 케라스 강좌 01강 - OT
- 딥러닝 케라스 강좌 02-1강 DNN #1
- 딥러닝 케라스 강좌 02-2강 DNN #2
- 머신러닝, 딥러닝 실전 개발 입문 24강 - Keras 기본
- Computer Graphics and Deep Learning with NeRF using TensorFlow and Keras: Part 1 - PyImageSearch
- 7 Best Keras Online Courses You Need to Know Bestseller 2022
- Implementation BEGAN by Keras
- 쌩(?!)초보자의 Python 케라스(Keras) GAN 코드 분석 (draft)
- A collection of Keras GAN notebooks
- Keras Adversarial Models
- How to Implement CycleGAN Models From Scratch With Keras
- Keras-BiGAN - BiGAN implementation in Keras to detect similarities in Landscapes
- Installing Keras for deep learning
- 텐서플로우, 티아노, 케라스 오프라인 설치 (주피터 포함)
- Tensorflow 및 Keras Offline 설치 순서
- Data Science for Startups: Deep Learning 설치부터 기초까지
- 케라스 설치
conda install -c anaconda keras-gpu- Installing TensorFlow 2.4, Keras, & Python 3.8 in Mac OSX
- AutoKeras: An AutoML system based on Keras
- An AutoML system based on Keras
- Auto-Keras - an open source software library for automated machine learning (AutoML)
- Auto-Keras, or How You can Create a Deep Learning Model in 4 Lines of Code
- AutoKeras: The Killer of Google’s AutoML
- 오토케라스 (Auto Keras) 소개 - 오픈소스 automl 실습
- Auto-keras 이용하기
- Why Is Auto-Keras Gaining Such Popularity?
- CNNGestureRecognizer ver 2.0 - Gesture recognition via CNN neural network implemented in Keras + Theano + OpenCV
- conditional_gan.py
- Elephas: Distributed Deep Learning with Keras & Spark
- gcnn_keras: Graph convolution with tf.keras
- Importance Sampling for Keras
- Kapre — Keras Audio Preprocessors - compute STFT, InverseSTFT, Melspectrogram, and others on GPU real-time
- keras_application_3D
- keras-bert - Implementation of BERT that could load official pre-trained models for feature extraction and prediction
- keras-inception-resnet-v2
- Keras Project Template - A project template to simplify building and training deep learning models using Keras
- Keras Tuner - An hyperparameter tuner for Keras, specifically for tf.keras with TensorFlow 2.0
- ktrain: a lightweight wrapper for Keras to help train (and deploy) neural networks
- plaidML-Keras
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mac 에서 딥러닝을 하는 방법은 크게, 1. CPU 이용, 2. PlaidML + OpenCL 이용, 3. ROCm (RadeonOpenCompute) 이용, 4. eGPU enclosure + NVIDIA GPU
- CPU는 느린 속도, 3/4번의 경우 어려운 셋업 및 macos 버전에 따른 문제(mavericks 및 catalina 버전에서는 사실상 불가능)
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PlaidML 은 Intel 에서 리드하는 프레임워크. NVIDIA/AMD 및 CPU 하드웨어가 각각에 맞는 OpenCL로 추상화 된 것을 다시한번 통합 추상화
-
PlaidML-Keras 라는 프로젝트가 있어서, PlaidML를 백엔드로 동작하는 Keras의 사용이 2017년경 부터 가능. 현재까지도 지속적으로 업데이트 되어 Keras 2.x 까지 지원
-
Apple/macos 진영에서는 수년 전 부터 Metal 이라는 프레임워크를 개발. Metal 은 AMD GPU를 제어하기 위한 API를 제공하는 매우 저 수준의 프레임워크. 현재 애플의 모든 상품에 적용이 되어 왔고, OpenCL은 사실상 Deprecated
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Metal이 적용된 여러가지 killing 애플리케이션의 성능이 OpenCL에 비해서 월등히 향상
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PlaidML-Keras 프로젝트에서는 2018년 5월경 부터 OpenCL과 더불이 Metal 의 지원을 런칭. AMD Radeon GPU 활용하여, Metal의 고성능 프레임워크를 백엔드로, Keras API를 사용한 딥러닝 가능
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더불어, Mac 컴퓨터에 eGPU를 연결해서 하이엔드급 Radeon GPU의 연결도 가능합니다
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사용 방법
1. pip install -U plaidml-keras 2. plaidml-setup 여기서 OpenCL 대신, metal 선택 3. Python 코드 작성 import os os.environ["KERAS_BACKEND"] = "plaidml.keras.backend" 위의 내용 입력 후, import keras 하여 평소 쓰던대로 사용 -
Announcing PlaidML: Open Source Deep Learning for Every Platform
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- reactionrnn - a Python 2/3 module + R package on top of Keras/TensorFlow which can easily predict the proportionate reactions (love, wow, haha, sad, angry) to a given text using a pretrained recurrent neural network
- Spektral - a framework for relational representation learning, built in Python and based on the Keras API Deep learning on graphs with Keras
- SupervisedChromeTrex - Chrome Browser's TRex self playing AI via CNN neural network implemented in Keras + Theano + OpenCV
- 파이썬 케라스로 딥러닝하자! LSTM(RNN)을 이용해 뉴스 기사 분류하기
- Understand the Difference Between Return Sequences and Return States for LSTMs in Keras
- A Gentle Introduction to LSTM Autoencoders
- LSTM Autoencoder for Extreme Rare Event Classification in Keras
- Denoising autoencoders with Keras, TensorFlow, and Deep Learning - PyImageSearch
- 딥러닝을 활용한 거래량 예측 기능 개선 LSTM
- Predicting sequences of vectors (regression) in Keras using RNN - LSTM
- Text Generation With LSTM Recurrent Neural Networks in Python with Keras
- An applied introduction to LSTMs for text generation — using Keras and GPU-enabled Kaggle Kernels
- Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras
- Keras LSTMs
- Learning Math with LSTMs and Keras
- Sequence Classification with LSTM Recurrent Neural Networks in Python with Keras
- 순환 신경망 레이어 및 기본 모델 이야기
- how to train a many to many sequence labeling using LSTM and BLSTM respectively?
- Sequence Classification with LSTM Recurrent Neural Networks in Python with Keras
- How to Generate Music using a LSTM Neural Network in Keras
- understanding lstm and its quick implementation in keras for sentiment analysis
- How to predict Bitcoin and Ethereum price with RNN-LSTM in Keras
- 케라스 LSTM 모델로 작곡하기
- How to Develop LSTM Models for Multi-Step Time Series Forecasting of Household Power Consumption
- Choosing the right Hyperparameters for a simple LSTM using Keras
- Stateful LSTM in Keras
- Keras에서 Sequence를 이용하여 대용량 데이터셋 처리하기 | KWANGSIK LEE's log
- Deep Learning: Keras Short Tutorial
- KEKOxTutorial
- Keras: Theano-based Deep Learning library
- What are good resources/tutorials to learn Keras (deep learning library in Python)?
- Regression Tutorial with the Keras Deep Learning Library in Python
- Tutorial: Optimizing Neural Networks using Keras (with Image recognition case study)
- Keras-Tutorials - Simple tutorials using Keras Framework
- Keras Tutorial: The Ultimate Beginner’s Guide to Deep Learning in Python
- Keras CNN tutorial
- Image denoising with Autoencoder in Keras
- Keras Tutorial: Content Based Image Retrieval Using a Convolutional Denoising Autoencoder
- Keras resources - This is a directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library
- Introducing Keras 2
- Introduction to Deep Learning - Deep Learning basics with Python, TensorFlow and Keras p.1
- Deep Learning with Python, TensorFlow, and Keras tutorial
- Loading in your own data - Deep Learning basics with Python, TensorFlow and Keras p.2
- Convolutional Neural Networks - Deep Learning basics with Python, TensorFlow and Keras p.3
- Analyzing Models with TensorBoard - Deep Learning with Python, TensorFlow and Keras p.4
- Optimizing with TensorBoard - Deep Learning w/ Python, TensorFlow & Keras p.5
- How to use your trained model - Deep Learning basics with Python, TensorFlow and Keras p.6
- Recurrent Neural Networks (RNN) - Deep Learning w/ Python, TensorFlow & Keras p.7
- Keras Tutorial: Deep Learning in Python
- Keras Tensorflow tutorial: Practical guide from getting started to developing complex deep neural network
- DEvol - Deep Neural Network Evolution
- Object detection with neural networks — a simple tutorial using keras
- Binary Classification Tutorial with the Keras Deep Learning Library
- Keras Tutorial - Spoken Language Understanding
- Autonomous Driving using End-to-End Deep Learning: an AirSim tutorial
- DeepLearning_Basic_Tutorial
- Keras_Tutorial_PCJ colab
- 초급자를 위한 기본적인 코드 참고용
- 15min Tutorial : keras + CNN + MNIST + Colab
- Keras 101: A simple (and interpretable) Neural Network model for House Pricing regression
- Keras with TensorFlow Course - Python Deep Learning and Neural Networks
- TensorFlow, Keras and deep learning, without a PhD
- Keras Tutorial With TensorFlow | Building Deep Learning Models With Python