文件名称：TensorFlow_certification:Cousera课程以获取TensorFlow Developer认证
文件大小：10.46MB
文件格式：ZIP
更新时间：2024-04-07 23:09:47
JupyterNotebook
TensorFlow_certification:Cousera课程以获取TensorFlow Developer认证
【文件预览】：
TensorFlow_certification-main
----Convolutional neural networks in tensorflow()
--------Cats and Dogs-Augmentation.ipynb(1.57MB)
--------Exercise_4_Multi_class_classifier_Question-FINAL.ipynb(45KB)
--------Exercise_3_Horses_vs_humans_using_Transfer_Learning_Question-FINAL.ipynb(158KB)
--------Exercise_1_Cats_vs_Dogs_Question-FINAL.ipynb(35KB)
--------test_images()
--------Augmentation.ipynb(1KB)
--------Exercise_2_Cats_vs_Dogs_using_augmentation_Question-FINAL.ipynb(33KB)
--------Multi-class Rock Paper Scissors.ipynb(324KB)
--------Transfer Learning.ipynb(34KB)
--------.ipynb_checkpoints()
--------Cats and Dogs.ipynb(1.68MB)
----Introduction to TensorFlow for Artificial Intelligence()
--------MNIST_Fashion_Dataset Model .ipynb(19KB)
--------Implementing convolutional layers.ipynb(24KB)
--------Exercise2-Question.ipynb(7KB)
--------Horse_Human_classifier.ipynb(1.68MB)
--------Course_1_Part_6_Lesson_3_Notebook.ipynb(285KB)
--------test_images()
--------Exercise4-Question.ipynb(8KB)
--------Hello World - Exercise 1 .ipynb(85KB)
--------.ipynb_checkpoints()
--------Horse_Human_classifier_with_validation_150.ipynb(1.73MB)
----Natural Language Processing in tensorflow()
--------meta.tsv(6KB)
--------Exercise_3_Exploring_overfitting_in_NLP_Question-FINAL.ipynb(51KB)
--------Exercise_1_Explore_the_BBC_news_archive_Question-FINAL.ipynb(35KB)
--------LSTM code.ipynb(4KB)
--------Multiple layer GRU.ipynb(124KB)
--------Single LSTM.ipynb(54KB)
--------tokenizer subwords8k .ipynb(4KB)
--------Exercise_2_BBC_news_archive_Question-FINAL.ipynb(60KB)
--------1D convolution.ipynb(53KB)
--------Sarcasm model.ipynb(8KB)
--------Multiple LSTM.ipynb(125KB)
--------Sarcasm identification.ipynb(3KB)
--------vecs.tsv(180KB)
--------Sequence prediction.ipynb(18KB)
--------.ipynb_checkpoints()
--------Intro to text encodings.ipynb(3KB)
--------IMDB dataset.ipynb(10KB)
----.gitignore(75B)