Posts by Tag

• keras 20
• tensorflow 2.0 17
• 논문 읽기 8
• 전처리 5
• tokenizer 5
• RNN 4
• OOV 4
• tensorflow 3
• NLP 2
• 톺아보기 2
• spyder 2
• GPU 2
• custom modeling 2
• Inference 2
• update 1
• text data augmentation 1
• database 1
• mysql 1
• autoencoder 1
• adversarial 1
• GAN 1
• ELBO 1
• Mac OS 1
• mathjax 1
• semi-supervised 1
• slurm 1
• sbatch 1
• pytorch 1
• python 1
• vscode 1

keras

DENSITY ESTIMATION USING REAL NVP

3 minute read

Real NVP를 tensorflow로 구현하기

Custom loss와 model.fit()을 같이 사용해보자!

1 minute read

가중치에 MCP penalty가 적용된 신경망 모형을 구현해보자!

5 minute read

custom kernel regularizer를 구현하기

가중치가 반복되는 Fully Connected Layer 만들기

1 minute read

Semi-supervised learning with deep generative models Review

less than 1 minute read

tensorflow 2.0으로 구현해보자!

Gumbel-Softmax Review

less than 1 minute read

tensorflow 2.0으로 구현해보자!

Generating Sentences from a Continuous Space 1편

2 minute read

VAE + RNN을 알아보자

seq2seq 톺아보기 (1)

5 minute read

Introduction & RNN(Recurrent Neural Network)

Save and Serialize Models

6 minute read

모형의 저장과 직렬화

Train and Evaluate with Keras (3)

6 minute read

Part 2(everything from scratch)

Train and Evaluate with Keras (2)

10 minute read

Part 1, 2부(multi-inputs and outputs, callback, checkpoint)

Layer Class in Keras

2 minute read

Keras의 Layer Class

Train and Evaluate with Keras (1)

9 minute read

Part 1, 1부(loss, metric, optimizer)

Keras functional API (2)

5 minute read

Keras functional API 2부

Keras functional API (1)

4 minute read

Keras functional API 1부

RNN with Keras (2)

2 minute read

Keras RNN의 더 많은 특징

RNN with Keras (1)

5 minute read

Keras RNN의 기초

Custom modeling with Keras (3)

4 minute read

모형의 적합!

Custom modeling with Keras (2)

2 minute read

loss, config and serialization

Custom modeling with Keras (1)

3 minute read

기초적인 custom 모형 제작 방법

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tensorflow 2.0

DENSITY ESTIMATION USING REAL NVP

3 minute read

Real NVP를 tensorflow로 구현하기

Custom loss와 model.fit()을 같이 사용해보자!

1 minute read

가중치에 MCP penalty가 적용된 신경망 모형을 구현해보자!

5 minute read

custom kernel regularizer를 구현하기

가중치가 반복되는 Fully Connected Layer 만들기

1 minute read

seq2seq 톺아보기 (1)

5 minute read

Introduction & RNN(Recurrent Neural Network)

Save and Serialize Models

6 minute read

모형의 저장과 직렬화

Train and Evaluate with Keras (3)

6 minute read

Part 2(everything from scratch)

Train and Evaluate with Keras (2)

10 minute read

Part 1, 2부(multi-inputs and outputs, callback, checkpoint)

Layer Class in Keras

2 minute read

Keras의 Layer Class

Train and Evaluate with Keras (1)

9 minute read

Part 1, 1부(loss, metric, optimizer)

Keras functional API (2)

5 minute read

Keras functional API 2부

Keras functional API (1)

4 minute read

Keras functional API 1부

RNN with Keras (2)

2 minute read

Keras RNN의 더 많은 특징

RNN with Keras (1)

5 minute read

Keras RNN의 기초

Custom modeling with Keras (3)

4 minute read

모형의 적합!

Custom modeling with Keras (2)

2 minute read

loss, config and serialization

Custom modeling with Keras (1)

3 minute read

기초적인 custom 모형 제작 방법

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논문 읽기

Assessing Partial Association Between Ordinal Variables: Quantification, Visualization, and Hypothesis Testing (논문 읽기)

1 minute read

Ordinal variable 사이에 association 계산하기

Distance-Based Analysis of Ordinal Data and Ordinal Time Series (논문 읽기)

2 minute read

Ordinal data에 대해 정의되는 거리 함수를 이해하기

Collaborative Multilabel Classification (논문 읽기)

3 minute read

With semi-supervised learning consistency regularization

ALMOND (논문 읽기)

2 minute read

Adaptive Latent Modeling and Optimization via Neural Networks and Langevin Diffusion

Layer Normalization(논문 읽기)

less than 1 minute read

Layer Normalization과 Batch Normalization을 비교해보자!

Deep Residual Learning Networks(논문 읽기)

less than 1 minute read

ResNet 알아보기

Subword Regularization(논문 읽기)

5 minute read

Improving Neural Network Translation Models with Multiple Subword Candidates

Neural Machine Translation of Rare Words with Subword Units(논문 읽기)

2 minute read

Byte Pair Encoding을 활용한 OOV 해결

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전처리

Subword Regularization(논문 읽기)

5 minute read

Improving Neural Network Translation Models with Multiple Subword Candidates

Byte Pair Encoding (2)

4 minute read

실제 데이터 적용하기

Neural Machine Translation of Rare Words with Subword Units(논문 읽기)

2 minute read

Byte Pair Encoding을 활용한 OOV 해결

Byte Pair Encoding (1)

3 minute read

BPE의 개념

전처리 workflow

9 minute read

품사 기반 전처리의 overview

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tokenizer

Subword Regularization(논문 읽기)

5 minute read

Improving Neural Network Translation Models with Multiple Subword Candidates

Byte Pair Encoding (2)

4 minute read

실제 데이터 적용하기

Neural Machine Translation of Rare Words with Subword Units(논문 읽기)

2 minute read

Byte Pair Encoding을 활용한 OOV 해결

Byte Pair Encoding (1)

3 minute read

BPE의 개념

전처리 workflow

9 minute read

품사 기반 전처리의 overview

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RNN

Generating Sentences from a Continuous Space 1편

2 minute read

VAE + RNN을 알아보자

seq2seq 톺아보기 (1)

5 minute read

Introduction & RNN(Recurrent Neural Network)

RNN with Keras (2)

2 minute read

Keras RNN의 더 많은 특징

RNN with Keras (1)

5 minute read

Keras RNN의 기초

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OOV

Subword Regularization(논문 읽기)

5 minute read

Improving Neural Network Translation Models with Multiple Subword Candidates

Byte Pair Encoding (2)

4 minute read

실제 데이터 적용하기

Neural Machine Translation of Rare Words with Subword Units(논문 읽기)

2 minute read

Byte Pair Encoding을 활용한 OOV 해결

Byte Pair Encoding (1)

3 minute read

BPE의 개념

Back to Top ↑

tensorflow

Semi-supervised learning with deep generative models Review

less than 1 minute read

tensorflow 2.0으로 구현해보자!

Gumbel-Softmax Review

less than 1 minute read

tensorflow 2.0으로 구현해보자!

Generating Sentences from a Continuous Space 1편

2 minute read

VAE + RNN을 알아보자

Back to Top ↑

NLP

RNN with Keras (2)

2 minute read

Keras RNN의 더 많은 특징

RNN with Keras (1)

5 minute read

Keras RNN의 기초

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톺아보기

Text Data Augmentation Made Simple By Leveraging NLP Cloud APIs(논문 읽기)

3 minute read

Text Data Augmentation

seq2seq 톺아보기 (1)

5 minute read

Introduction & RNN(Recurrent Neural Network)

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spyder

Probabilistic CCA with implicit distributions

7 minute read

ACCA를 python 코드로 구현해보기!

Spyder Remote Kernel

6 minute read

server 컴퓨터의 환경을 원격으로 사용하자!

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GPU

SLURM JOB SCHEDULER

less than 1 minute read

server 환경에서 python 코드 구동하기

ubuntu 18.04 LTS DeepLearning Setting

2 minute read

tensorflow 2.0 GPU를 ubuntu에서 써보자!

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custom modeling

Custom loss와 model.fit()을 같이 사용해보자!

1 minute read

가중치에 MCP penalty가 적용된 신경망 모형을 구현해보자!

5 minute read

custom kernel regularizer를 구현하기

Back to Top ↑

Inference

Inference on Variable Importance Measure 2편

5 minute read

pytorch로 구현하기!

Inference on Variable Importance Measure 1편

4 minute read

Under Non-zero Null Hypothesis

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update

Welcome to Data Studio!

less than 1 minute read

Data Studio에 오신 것을 환영합니다!

Back to Top ↑

text data augmentation

Text Data Augmentation Made Simple By Leveraging NLP Cloud APIs(논문 읽기)

3 minute read

Text Data Augmentation

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database

MySQL을 R에서 사용해보자!

2 minute read

MySQL 활용하기

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mysql

MySQL을 R에서 사용해보자!

2 minute read

MySQL 활용하기

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autoencoder

Probabilistic CCA with implicit distributions

7 minute read

ACCA를 python 코드로 구현해보기!

Back to Top ↑

adversarial

Probabilistic CCA with implicit distributions

7 minute read

ACCA를 python 코드로 구현해보기!

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GAN

Probabilistic CCA with implicit distributions

7 minute read

ACCA를 python 코드로 구현해보기!

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ELBO

VAE Notes and Don’t Blame the ELBO! Review

2 minute read

Note on VAE and paper review

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Mac OS

[Mac OS] .DS_Store 파일 제거하기

less than 1 minute read

.DS_Store 파일을 제거하고 github에 commit을 막는 방법

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mathjax

github.io 수식 오류 해결하기!

1 minute read

mathjax를 사용할 때 수식이 제대로 보이지 않는 경우의 해결법

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semi-supervised

Semi-supervised learning with deep generative models Review

less than 1 minute read

tensorflow 2.0으로 구현해보자!

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slurm

SLURM JOB SCHEDULER

less than 1 minute read

server 환경에서 python 코드 구동하기

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sbatch

SLURM JOB SCHEDULER

less than 1 minute read

server 환경에서 python 코드 구동하기

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pytorch

Inference on Variable Importance Measure 2편

5 minute read

pytorch로 구현하기!

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python

python과 Visual Studio Code 활용하기

1 minute read

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vscode

python과 Visual Studio Code 활용하기

1 minute read

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