TensorFlowLecture

KO | EN

gitlite — search

#javascript #llm #go #golang #rust #deep-learning #linux #java #windows #kubernetes #awesome-list #security #ios #open-source

TensorFlowLecture

(★ 32)

To make those tutorials, I referred to several tutorials including open courses, YouTube, and Books.

TensorFlowLecture 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# TensorFlowLecture

여러 강의와 교재를 보고 작성한 예제 코드들 입니다.
이론적인 정리 내용은 저의 개인 [블로그](http://goodtogreate.tistory.com/category/Data%20Science/TensorFlow%20%28python%29)에 있습니다.

## 개발환경 ##

- Ubuntu 16.04
- Pycharm Pro and Jupyter Notebook
- Python 3.5
- Tensor Flow 1.4

## 목차 ##

### Numpy, Scipy 코드 ###

0.1. [Fundamental_Neural_Network](https://github.com/leejaymin/TensorFlowLecture/tree/master/0.1.Fundamental_Neural_Network)

### TensorFlow 코드 ###
0. [Basic Example](https://github.com/leejaymin/TensorFlowLecture/tree/master/0.2.Basic)
1. [Linear Regression](https://github.com/leejaymin/TensorFlowLecture/tree/master/1.Linear%20Regression)
1. [Logistic Classification](https://github.com/leejaymin/TensorFlowLecture/tree/master/2.Logistic%20Classification)
1. [Multiple Perceptron for XOR Problem](https://github.com/leejaymin/TensorFlowLecture/tree/master/3.XOR)
1. [MNIST set](https://github.com/leejaymin/TensorFlowLecture/tree/master/4.MNIST)
    - [Softmax classification](https://github.com/leejaymin/TensorFlowLecture/blob/master/4.MNIST/MNIST_Tutorial_DNN.ipynb)
    - [DNN with ReLU](https://github.com/leejaymin/TensorFlowLecture/blob/master/4.MNIST/MNIST_Tutorial_DNN.ipynb)
    - [DNN with Dropout and xavier_init](https://github.com/leejaymin/TensorFlowLecture/blob/master/4.MNIST/MNIST_Tutorial_DNN.ipynb)
1. [CNN](https://github.com/leejaymin/TensorFlowLecture/tree/master/5.CNN)
1. [Early Stop and Index Shuffling](https://github.com/leejaymin/TensorFlowLecture/tree/master/6.Early%20Stop%20and%20Index%20Shuffling)
1. [TensorBoard](https://github.com/leejaymin/TensorFlowLecture/tree/master/7.TensorBoard)
1. [Save and Restore](https://github.com/leejaymin/TensorFlowLecture/tree/master/8.Save%20and%20Restore)
1. [RNN](https://github.com/leejaymin/TensorFlowLecture/tree/master/9.RNN)
1. [Transfer Learning](https://github.com/leejaymin/TensorFlowLecture/tree/master/10.Transfer%20Learning)

## 참고자료 ##
- Coursera, Machine Learning (Andrew ng): [URL](https://www.coursera.org/learn/machine-learning/home/welcome) 
- Python으로 구현된 코세라 숙제 코드: [URL](https://github.com/kaleko/CourseraML)  
- 김성훈 교수님 강의 페이지: [URL](http://hunkim.github.io/ml/) 
- 구글 공식 TensorFlow 튜토리얼: [URL](https://www.tensorflow.org/get_started/)
- Bay Area DL School Live Stream, Sherry Moore, tf-tutorial: [URL](https://github.com/sherrym/tf-tutorial)  
- 텐서플로 코리아: [URL](https://tensorflowkorea.wordpress.com/)  
- 한국인지과학협회 딥러닝 튜토리얼: [URL](https://github.com/leejaymin/deeplearning_tutorial) 
- tgjeon, TensorFlow-Tutorials-for-Time-Series: [URL](https://github.com/tgjeon/TensorFlow-Tutorials-for-Time-Series)

TensorFlowLecture

TensorFlowLecture 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

TensorFlowLecture

TensorFlowLecture 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README