Neural network projects with Python : the ultimate guide to using Python to explore the true power of neural networks through six projects / James Loy.

By:

Loy, James [author.]

Material type: Text

TextPublisher: Birmingham, UK : Packt Publishing, 2019Description: 1 online resource (v, 295 pages) : illustrationsContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781789133318
1789133319

Subject(s): Genre/Form:

Additional physical formats: Print version:: Neural network projects with Python : the ultimate guide to using Python to explore the true power of neural networks through six projects.DDC classification:

005.133 23

LOC classification:

QA76.73.P98

Online resources:

Click here to access online

Contents:

Table of ContentsMachine Learning and Neural Networks 101Predicting Diabetes with Multilayer PerceptronsPredicting Taxi Fares with Deep Feedforward NetworksCats Versus Dogs -- Image Classification Using CNNsRemoving Noise from Images Using AutoencodersSentiment Analysis of Movie Reviews Using LSTMImplementing a Facial Recognition System with Neural NetworksWhat's Next?

Abstract: Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio.

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Item type	Home library	Collection	Call number	Materials specified	Status	Date due	Barcode
Electronic-Books	OPJGU Sonepat- Campus	E-Books EBSCO			Available

Online resource; title from title page (Safari, viewed April 18, 2019).

Includes index.

Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio.

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