/Tensorflow-Advanced-Techniques-Specialization

TensorFlow: Advanced Techniques Specialization by Laurence Moroney, and Eddy Shyu in Coursera by DeapLearning.AI

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Tensorflow: Advanced Techniques Specialization


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This is my assignment in that specialization. This repo only includes lab files, and assignment files in all classes (and all weeks). If you want to ask about this repo, feel free to contact me

You can also get all the raw files in here

Table of Content

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├── Advanced Computer Vision with Tensorflow
│   ├── Week 1
│   │   ├── C3W1_Assignment.ipynb
│   │   ├── C3_W1_Lab_1_transfer_learning_cats_dogs.ipynb
│   │   ├── C3_W1_Lab_2_Transfer_Learning_CIFAR_10.ipynb
│   │   └── C3_W1_Lab_3_Object_Localization.ipynb
│   └── Week 2
│       ├── C3_W2_Lab_1_Simple_Object_Detection.ipynb
│       └── C3_W2_Lab_2_Object_Detection.ipynb
├── Custom Models, Layers, Loss Functions with Tensorflow
│   ├── Week 1
│   │   ├── C1W1_Assignment.ipynb
│   │   ├── C1_W1_Lab_1_functional-practice.ipynb
│   │   ├── C1_W1_Lab_2_multi-output.ipynb
│   │   ├── C1_W1_Lab_3_siamese-network.ipynb
│   │   ├── data
│   │   │   └── ENB2012_data.xlsx
│   │   ├── utils.py
│   │   ├── winequality-red.csv
│   │   └── winequality-white.csv
│   ├── Week 2
│   │   ├── C1W2_Assignment.ipynb
│   │   ├── C1_W2_Lab_1_huber_loss.ipynb
│   │   ├── C1_W2_Lab_2_huber_object_loss.ipynb
│   │   └── utils.py
│   ├── Week 3
│   │   ├── C1W3_Assignment.ipynb
│   │   ├── C1_W3_Lab_1_lambda_layer.ipynb
│   │   ├── C1_W3_Lab_2_custom-dense-layer.ipynb
│   │   ├── C1_W3_Lab_3_custom_layer_activation.ipynb
│   │   └── utils.py
│   ├── Week 4
│   │   ├── C1W4_Assignment.ipynb
│   │   ├── C1_W4_Lab_1_basic_model.ipynb
│   │   ├── C1_W4_Lab_2_resnet_example.ipynb
│   │   ├── VGG.png
│   │   └── utils.py
│   └── Week 5
│       ├── C1_W5_Lab_1_exploring_callbacks.ipynb
│       ├── C1_W5_Lab_2_custom_callbacks.ipynb
│       └── animation.gif
└── Custom and Distributed Training with Tensorflow
    ├── Week 1
    │   ├── C2W1_Assignment.ipynb
    │   ├── C2_W1.pdf
    │   ├── C2_W1_Lab_1_basic_tensors.ipynb
    │   └── C2_W1_Lab_2_gradient_tape_basics.ipynb
    ├── Week 2
    │   ├── C2W2_Assignment.ipynb
    │   ├── C2_W2.pdf
    │   ├── C2_W2_Lab_1_training_basics.ipynb
    │   ├── C2_W2_Lab_2_training_categorical.ipynb
    │   ├── data
    │   │   └── data.csv
    │   └── test_model
    │       ├── saved_model.pb
    │       └── variables
    │           ├── variables.data-00000-of-00001
    │           └── variables.index
    ├── Week 3
    │   ├── C2W3_Assignment.ipynb
    │   ├── C2_W3.pdf
    │   ├── C2_W3_Lab_1_autograph_basics.ipynb
    │   ├── C2_W3_Lab_2_graphs_for_complex_code.ipynb
    │   └── data
    │       └── resnet_50_feature_vector
    │           ├── saved_model.pb
    │           └── variables
    │               ├── variables.data-00000-of-00001
    │               └── variables.index
    └── Week 4
        ├── C2W4_Assignment.ipynb
        ├── C2_W4.pdf
        ├── C2_W4_Lab_1_basic_mirrored_strategy.ipynb
        ├── C2_W4_Lab_2_multi_GPU_mirrored_strategy.ipynb
        ├── C2_W4_Lab_3_using_TPU_strategy.ipynb
        ├── C2_W4_Lab_4_one_device_strategy.ipynb
        └── data