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[『텐서플로로 배우는 딥러닝』, 솔라리스, 영진닷컴, 2018] 도서의 소스코드입니다.

Python 89.25% Shell 0.19% Jupyter Notebook 10.55%

deep-learning-tensorflow-book-code's Introduction

『텐서플로로 배우는 딥러닝』 GitHub Repository

[『텐서플로로 배우는 딥러닝』, 솔라리스, 영진닷컴, 2018] 도서의 소스코드입니다.

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Chapter 2 - 텐서플로우 소개

Chapter 3 - 텐서플로우 기초와 텐서보드

Chapter 4 - 머신러닝 기초 이론들

  • 소프트맥스 회귀(Softmax Regression)를 이용한 MNIST 숫자분류기 (Code) (TF v2 Code)
  • tf.nn.sparse_softmax_cross_entropy_with_logits API를 사용한 소프트맥스 회귀(Softmax Regression)를 이용한 MNIST 숫자분류기 (Code) (TF v2 Code)

Chapter 5 - 인공신경망(Artificial Neural Networks) - ANN

Chapter 6 - 오토인코더(Autoencoder)

Chapter 7 - Convolutional Neural Networks(CNN)

Chapter 8 - Recurrent Neural Networks(RNN)

  • tf.nn.embedding_lookup을 이용한 Embedding 예제 (Code)
  • Gradient Clipping 예제 (Code)
  • Char-RNN을 이용한 텍스트 생성 (Code)

Chapter 9 - Image Captioning

  • im2txt - Show and Tell 모델 구현 (Code)

Chapter 10 - Semantic Image Segmentation

  • FCN.tensorflow - FCN(Fully Convolutional Networks) 모델 구현 (Code)

Chapter 11 - 생성모델(Generative Model) - GAN(Generative Adversarial Networks)

Chapter 12 - 강화학습(Reinforcement Learning)

Chapter 13 - 파인튜닝(Fine-Tuning)과 Pre-Trained 모델을 이용해서 실제 문제 해결하기

  • Inception v3 Retraining을 이용해서 나만의 분류기 만들어보기 (Code)
  • Pre-Trained 모델을 이용해서 Object Detection 수행하기 (Code)

Revision History

2019-10-27

  • Chapter 6,11 - TensorFlow 2.0 호환 코드 추가 - TF v2 Code

2019-10-18

  • Chapter 4,5,7 - TensorFlow 2.0 호환 코드 추가 - TF v2 Code

2019-10-06

  • Chapter 2,3 - TensorFlow 2.0 호환 코드 추가 - TF v2 Code

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