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Key benefits

Understand the nuances of setting up a deep learning programming environment

Gain insights into the common components of a neural network and its essential operations

Get to grips with deploying a machine learning model as an interactive web application with Flask

Description

Machine learning gives computers the ability to learn like humans. It is becoming increasingly transformational to businesses in many forms, and a key skill to learn to prepare for the future digital economy. As a beginner, you’ll unlock a world of opportunities by learning the techniques you need to contribute to the domains of machine learning, deep learning, and modern data analysis using the latest cutting-edge tools. The Applied TensorFlow and Keras Workshop begins by showing you how neural networks work. After you’ve understood the basics, you will train a few networks by altering their hyperparameters. To build on your skills, you’ll learn how to select the most appropriate model to solve the problem in hand. While tackling advanced concepts, you’ll discover how to assemble a deep learning system by bringing together all the essential elements necessary for building a basic deep learning system - data, model, and prediction. Finally, you’ll explore ways to evaluate the performance of your model, and improve it using techniques such as model evaluation and hyperparameter optimization. By the end of this book, you'll have learned how to build a Bitcoin app that predicts future prices, and be able to build your own models for other projects.

Who is this book for?

If you are a data scientist or a machine learning and deep learning enthusiast, who is looking to design, train, and deploy TensorFlow and Keras models into real-world applications, then this workshop is for you. Knowledge of computer science and machine learning concepts and experience in analyzing data will help you to understand the topics explained in this book with ease.

What you will learn

Familiarize yourself with the components of a neural network

Understand the different types of problems that can be solved using neural networks

Explore different ways to select the right architecture for your model

Make predictions with a trained model using TensorBoard

Discover the components of Keras and ways to leverage its features in your model

Explore how you can deal with new data by learning ways to retrain your model

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

The Applied TensorFlow and Keras Workshop

€24.99

€32.99

€29.99

Total € 87.97

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Rajeev Oct 01, 2020

I wasn't sure what to expect with this book. Overall I was surprised that it covered so many topics that aren't too common, but very important for practitioners out there. I loved the example projects using Bitcoin, also I loved the TensorBoard sections. The best part for me was the Productization Chapter which features some extremely useful information. Great book, also I should add that it covers the basics of Deep Learning from a theoretical and practical standpoint very well!

Amazon Verified review

nikesh Jan 15, 2021

The Applied Tensorflow and Keras Workshop is a simple yet powerful book for both beginner and moderate level readers in Data Science and Artificial Intelligence. The book uses a Bitcoin price prediction project to walk the reader through the basics of neural networks and building, training, and deploying models. This book is a good resource to learn model architecture considerations, their limitations, and the impact on model output. For instance, in one example, the authors compare the output of a fully connected model on the MNIST dataset with that of a convolution neural network. Each section of the book provides a link to the original research. The book also includes code files (python scripts) as well as an interactive lab environment. Areas of improvement: Some parts of the book require more explanation. Without such detail, beginners might find them hard to understand. For instance, 1) CNNs on page 35 and the vanishing gradient problem on page 99 can be explained in more detail. 2) For the bitcoin example in the second chapter, more explanation of the code is required.

The Applied TensorFlow and Keras Workshop: Develop your practical skills by working through a real-world project and build your own Bitcoin price prediction tracker

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