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TensorFlow MOOC Code Implementation 入门实操课程代码完整实现 TensorFlow官方社区联合中国MOOC出品

www.icourse163.org/course/youdao-1460578162

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horse_human_params/Final
horse_human_params/Final
 
 
Chapter-10.1-IMDB-Reviews.ipynb
Chapter-10.1-IMDB-Reviews.ipynb
 
 
Chapter-10.2-Sarcasm-Dectction.ipynb
Chapter-10.2-Sarcasm-Dectction.ipynb
 
 
Chapter-10.3-IMDB-Reviews-8k.ipynb
Chapter-10.3-IMDB-Reviews-8k.ipynb
 
 
Chapter-11.1-11.2-Text-Generator-with-RNN.ipynb
Chapter-11.1-11.2-Text-Generator-with-RNN.ipynb
 
 
Chapter-11.3-Article-Generator-with-Irish-Lyrics.ipynb
Chapter-11.3-Article-Generator-with-Irish-Lyrics.ipynb
 
 
Chapter-12.1-Time-Sequences.ipynb
Chapter-12.1-Time-Sequences.ipynb
 
 
Chapter-12.2-Predicting-Time-Sequences.ipynb
Chapter-12.2-Predicting-Time-Sequences.ipynb
 
 
Chapter-13-RNN-Sample-Generation.ipynb
Chapter-13-RNN-Sample-Generation.ipynb
 
 
Chapter-14-RNN-Model-Prediting-Time-Series.ipynb
Chapter-14-RNN-Model-Prediting-Time-Series.ipynb
 
 
Chapter-2-Fashion.ipynb
Chapter-2-Fashion.ipynb
 
 
Chapter-4-Horse-or-Human-with-tunner.ipynb
Chapter-4-Horse-or-Human-with-tunner.ipynb
 
 
Chapter-5-Classification-Cat-Dog.ipynb
Chapter-5-Classification-Cat-Dog.ipynb
 
 
Chapter-6-Horse-or-Human-without-tunner.ipynb
Chapter-6-Horse-or-Human-without-tunner.ipynb
 
 
Chapter-7-Number-MNIST.ipynb
Chapter-7-Number-MNIST.ipynb
 
 
Chapter-7-RPS.ipynb
Chapter-7-RPS.ipynb
 
 
Chapter-7-Sign-MNIST.ipynb
Chapter-7-Sign-MNIST.ipynb
 
 
Chapter-8-Tokenization-Serialization.ipynb
Chapter-8-Tokenization-Serialization.ipynb
 
 
Chapter-9.1-IMDB-Reviews-Dataset.ipynb
Chapter-9.1-IMDB-Reviews-Dataset.ipynb
 
 
Chapter-9.2-Embedding-Sarcasm-Detction-with-Tuning.ipynb
Chapter-9.2-Embedding-Sarcasm-Detction-with-Tuning.ipynb
 
 
Chapter-9.3-IMDB-Reviews-with-Pretokenization-Dataset.ipynb
Chapter-9.3-IMDB-Reviews-with-Pretokenization-Dataset.ipynb
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 
hps.h5
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Tensorflow-MOOC (TensorFlow 入门实操课程)

Chinese MOOC Courses URL:

https://www.icourse163.org/learn/youdao-1460578162#/learn/announce

Dataset Downloding Places:

Horses and Humans

https://storage.googleapis.com/laurencemoroney-blog.appspot.com/validation-horse-or-human.zip https://storage.googleapis.com/laurencemoroney-blog.appspot.com/horse-or-human.zip

Cat and Dog

https://download.microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_3367a.zip

Sign MNIST

https://www.kaggle.com/datamunge/sign-language-mnist/home

RPS

https://storage.googleapis.com/laurencemoroney-blog.appspot.com/rps.zip https://storage.googleapis.com/laurencemoroney-blog.appspot.com/rps-test-set.zip

News Headlines Dataset For Sarcasm Detection

https://storage.googleapis.com/laurencemoroney-blog.appspot.com/sarcasm.json

Text Generator

https://storage.googleapis.com/laurencemoroney-blog.appspot.com/irish-lyrics-eof.txt

https://storage.googleapis.com/laurencemoroney-blog.appspot.com/sonnets.txt

Notebooks Environment:

numpy

jupyter notebook

tensorflow >= 2.2.0

tensorflow_dataset >= 4.1.0

TensorFlow introductory practical course

  • Part 1: The first course in deep learning with TensorFlow
    • Chapter 2: Introduction to Computer Vision
    • Chapter 3: Introduction to convolution
    • Chapter 4: More complex image applications
  • Part 2: Machine Vision - Image Classification
    • Chapter 5: Basic Application of Image Classification
    • Chapter 6: Transfer Learning
    • Chapter 7: Image Multivariate Classification
  • Part 3: Natural Language Processing
    • Chapter 8: Entryization and Serialization
    • Chapter 9: Word Embedding
    • Chapter 10: Exploring Recurrent Neural Networks
    • Chapter 11: Text Generation
  • Part 4: Sequences, Time Series and Forecasting
    • Chapter 12: Sequences and Time Series
    • Chapter 13: How to generate RNN network samples
    • Chapter 14: RNN Time Series Prediction
    • Chapter 15: Bidirectional LSTM Time Prediction
  • Part 5: Introduction to TensorFlow Lite
    • Chapter 16: Introduction to TensorFlow Lite

TensorFlow 入门实操课程

  • 第一部分：TensorFlow深度学习的第一门课程
    • 第二章：计算机视觉介绍
    • 第三章：卷积介绍
    • 第四章：更复杂的图像应用
  • 第二部分：机器视觉 - 图像分类
    • 第五章：图像分类基础应用
    • 第六章：迁移学习
    • 第七章：图像多元分类
  • 第三部分：自然语言处理
    • 第八章：词条化和序列化
    • 第九章：词嵌入
    • 第十章：探索循环神经网络
    • 第十一章：文本生成
  • 第四部分：序列，时间序列和预测
    • 第十二章：序列和时间序列
    • 第十三章：RNN网络样本的生成方法
    • 第十四章：RNN时间序列预测
    • 第十五章：双向LSTM时间预测
  • 第五部分：TensorFlow Lite介绍
    • 第十六章：TensorFlow Lite 简介

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TensorFlow MOOC Code Implementation 入门实操课程代码完整实现 TensorFlow官方社区联合中国MOOC出品

www.icourse163.org/course/youdao-1460578162

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