In this section, we will build all the bits and pieces that are necessary for our test, so let's start off by defining the inputs that will be used to feed data to the computational graph.
- Title Page
- Copyright and Credits
- Packt Upsell
- Contributors
- Preface
- Data Science - A Birds' Eye View
- Data Modeling in Action - The Titanic Example
- Feature Engineering and Model Complexity – The Titanic Example Revisited
- Get Up and Running with TensorFlow
- TensorFlow in Action - Some Basic Examples
- Deep Feed-forward Neural Networks - Implementing Digit Classification
- Introduction to Convolutional Neural Networks
- Object Detection – CIFAR-10 Example
- Object Detection – Transfer Learning with CNNs
- Recurrent-Type Neural Networks - Language Modeling
- Representation Learning - Implementing Word Embeddings
- Neural Sentiment Analysis
- Autoencoders – Feature Extraction and Denoising
- Generative Adversarial Networks
- Face Generation and Handling Missing Labels
- Implementing Fish Recognition
- Other Books You May Enjoy
Building the model
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