https://github.com/rickiepark/ml-ko

머신러닝, 딥러닝 한글 번역 저장소
https://github.com/rickiepark/ml-ko

deep-learning keras machine-learning python scikit-learn tensorflow

Last synced: 11 days ago
JSON representation

머신러닝, 딥러닝 한글 번역 저장소

• Host: GitHub
• URL: https://github.com/rickiepark/ml-ko
• Owner: rickiepark
• License: mit
• Created: 2020-10-09T04:04:01.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2023-02-09T08:47:46.000Z (almost 2 years ago)
• Last Synced: 2023-09-10T23:01:02.491Z (over 1 year ago)
• Topics: deep-learning, keras, machine-learning, python, scikit-learn, tensorflow
• Language: HTML
• Homepage: http://ml-ko.kr
• Size: 59.3 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# ml-ko.kr: 머신러닝 & 딥러닝 한글 번역 모음

===================

*   [개발자를 위한 머신러닝&딥러닝](aiml4corders)

*   [구글 코랩(Colab) 사용법 (\[혼자 공부하는 머신러닝+딥러닝\]의 1장 2절)](https://preview2.hanbit.co.kr/books/swtr/#p=35)

*   [<구글 브레인 팀에게 배우는 딥러닝 with TensorFlow.js> 예제의 라이브 데모!](tfjs)

*   핸즈온 머신러닝 2:

    *   [넘파이 튜토리얼](homl2/tools_numpy.html)

    *   [맷플롯립 튜토리얼](homl2/tools_matplotlib.html)

    *   [판다스 튜토리얼](homl2/tools_pandas.html)

    *   [머신러닝 프로젝트 체크리스트](https://github.com/rickiepark/handson-ml2/blob/master/ml-project-checklist.md)

    *   [자동 미분](https://github.com/rickiepark/handson-ml2/blob/master/extra_autodiff.ipynb)

*   [회오리바람을 탄 파이썬](whirlwindtourpython/목차.html)(Whirlwind Tour of Python)

*   [파이썬 라이브러리를 활용한 머신러닝 1장, 2장](https://tensorflow.blog/%ed%8c%8c%ec%9d%b4%ec%8d%ac-%eb%a8%b8%ec%8b%a0%eb%9f%ac%eb%8b%9d/)

*   케라스 창시자에게 배우는 딥러닝

    *   [신경망과의 첫 만남](dl-with-python/2.1-a-first-look-at-a-neural-network.html)

    *   [영화 리뷰 분류: 이진 분류 예제](dl-with-python/3.4-classifying-movie-reviews.html)

    *   [뉴스 기사 분류: 다중 분류 문제](dl-with-python/3.5-classifying-newswires.html)

    *   [주택 가격 예측: 회귀 문제](dl-with-python/3.6-predicting-house-prices.html)

    *   [과대적합과 과소적합](dl-with-python/4.4-overfitting-and-underfitting.html)

    *   [합성곱 신경망 소개](dl-with-python/5.1-introduction-to-convnets.html)

    *   [소규모 데이터셋에서 컨브넷 사용하기](dl-with-python/5.2-using-convnets-with-small-datasets.html)

    *   [사전 훈련된 컨브넷 사용하기](dl-with-python/5.3-using-a-pretrained-convnet.html)

    *   [컨브넷의 학습 시각화하기](dl-with-python/5.4-visualizing-what-convnets-learn.html)

    *   [단어와 문자의 원-핫 인코딩](dl-with-python/6.1-one-hot-encoding-of-words-or-characters.html)

    *   [단어 임베딩 사용하기](dl-with-python/6.1-using-word-embeddings.html)

    *   [순환 신경망 이해하기](dl-with-python/6.2-understanding-recurrent-neural-networks.html)

    *   [순환 신경망의 고급 사용법](dl-with-python/6.3-advanced-usage-of-recurrent-neural-networks.html)

    *   [컨브넷을 사용한 시퀀스 처리](dl-with-python/6.4-sequence-processing-with-convnets.html)

    *   [LSTM으로 텍스트 생성하기](dl-with-python/8.1-text-generation-with-lstm.html)

    *   [딥드림](dl-with-python/8.2-deep-dream.html)

    *   [뉴럴 스타일 트랜스퍼](dl-with-python/8.3-neural-style-transfer.html)

    *   [이미지 생성](dl-with-python/8.4-generating-images-with-vaes.html)

    *   [적대적 생성 신경망 소개](dl-with-python/8.5-introduction-to-gans.html)