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  • Book Overview & Buying The TensorFlow Workshop
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The TensorFlow Workshop

The TensorFlow Workshop

By : Matthew Moocarme, Abhranshu Bagchi, Anthony So , Anthony Maddalone
4.6 (25)
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The TensorFlow Workshop

The TensorFlow Workshop

4.6 (25)
By: Matthew Moocarme, Abhranshu Bagchi, Anthony So , Anthony Maddalone

Overview of this book

Getting to grips with tensors, deep learning, and neural networks can be intimidating and confusing for anyone, no matter their experience level. The breadth of information out there, often written at a very high level and aimed at advanced practitioners, can make getting started even more challenging. If this sounds familiar to you, The TensorFlow Workshop is here to help. Combining clear explanations, realistic examples, and plenty of hands-on practice, it’ll quickly get you up and running. You’ll start off with the basics – learning how to load data into TensorFlow, perform tensor operations, and utilize common optimizers and activation functions. As you progress, you’ll experiment with different TensorFlow development tools, including TensorBoard, TensorFlow Hub, and Google Colab, before moving on to solve regression and classification problems with sequential models. Building on this solid foundation, you’ll learn how to tune models and work with different types of neural network, getting hands-on with real-world deep learning applications such as text encoding, temperature forecasting, image augmentation, and audio processing. By the end of this deep learning book, you’ll have the skills, knowledge, and confidence to tackle your own ambitious deep learning projects with TensorFlow.
Table of Contents (13 chapters)
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Preface

Summary

In this chapter, you were introduced to the TensorFlow library. You learned how to use it in the Python programming language. You created the building blocks of ANNs (tensors) with various ranks and shapes, performed linear transformations on tensors using TensorFlow, and implemented addition, reshaping, transposition, and multiplication on tensors—all of which are fundamental for understanding the underlying mathematics of ANNs.

In the next chapter, you will improve your understanding of tensors and learn how to load data of various types and pre-process it such that it is appropriate for training ANNs in TensorFlow. You will work with tabular, visual, and textual data, all of which must be pre-processed differently. By working with visual data (that is, images), you will also learn how to use training data in which the size of the training data cannot fit into memory.

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The TensorFlow Workshop
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