Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Learning Hub

Conferences

Free Learning

Hands-On Neural Networks: Learn how to build and train your first neural network model using Python

Leonardo De Marchi

Laura Mitchell

$19.99 per month

3.5 (2 Ratings)

Paperback May 2019 280 pages 1st Edition

Leonardo De Marchi

Laura Mitchell

$19.99 per month

3.5 (2 Ratings)

Paperback May 2019 280 pages 1st Edition

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!

Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!

50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.

Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.

Thousands of reference materials covering every tech concept you need to stay up to date.

Subscribe now

View plans & pricing

View table of contents

Preview Book

Download Code

Key benefits

Explore neural network architecture and understand how it functions
Learn algorithms to solve common problems using backpropagation and perceptrons
Understand how to apply neural networks to applications with the help of useful illustrations

Description

Neural networks play a very important role in deep learning and artificial intelligence (AI), with applications in a wide variety of domains, right from medical diagnosis, to financial forecasting, and even machine diagnostics. Hands-On Neural Networks is designed to guide you through learning about neural networks in a practical way. The book will get you started by giving you a brief introduction to perceptron networks. You will then gain insights into machine learning and also understand what the future of AI could look like. Next, you will study how embeddings can be used to process textual data and the role of long short-term memory networks (LSTMs) in helping you solve common natural language processing (NLP) problems. The later chapters will demonstrate how you can implement advanced concepts including transfer learning, generative adversarial networks (GANs), autoencoders, and reinforcement learning. Finally, you can look forward to further content on the latest advancements in the field of neural networks. By the end of this book, you will have the skills you need to build, train, and optimize your own neural network model that can be used to provide predictable solutions.

Who is this book for?

If you are interested in artificial intelligence and deep learning and want to further your skills, then this intermediate-level book is for you. Some knowledge of statistics will help you get the most out of this book.

What you will learn

Learn how to train a network by using backpropagation
Discover how to load and transform images for use in neural networks
Study how neural networks can be applied to a varied set of applications
Solve common challenges faced in neural network development
Understand transfer learning concepts to solve tasks using Keras and Visual Geometry Group (VGG) network
Get up to speed with advanced and complex deep learning concepts such as LSTMs and natural language processing (NLP)
Explore innovative algorithms including GANs and deep reinforcement learning

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!

Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!

50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.

Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.

Thousands of reference materials covering every tech concept you need to stay up to date.

Subscribe now

View plans & pricing

Product Details

Publication date : May 30, 2019

Length: 280 pages

Edition : 1st

Language : English

ISBN-13 : 9781788992596

Vendor :

Google

Category :

Data

Languages :

Python

Concepts :

Neural Networks

Tools :

Keras

Frequently bought together

Hands-On Deep Learning Algorithms with Python

Jul 2019 512 pages

4.1 (13)

eBook

$9.99 ~~$26.99~~

Applied Unsupervised Learning with Python

May 2019 482 pages

3 (2)

eBook

$9.99 ~~$35.99~~

Hands-On Neural Networks

May 2019 280 pages

3.5 (2)

eBook

$9.99 ~~$26.99~~

Total $ 126.97

$38.99

$48.99

$38.99

Total $ 126.97

15 Chapters

Section 1: Getting Started

Getting Started with Supervised Learning

History of AI

An overview of machine learning

Environment setup

Supervised learning in practice with Python

Feature engineering

Supervised learning algorithms

Summary

Neural Network Fundamentals

The perceptron

Keras

Feedforward neural networks

FFNN in Python from scratch

Summary

Section 2: Deep Learning Applications

Convolutional Neural Networks for Image Processing

Understanding CNNs

Convolutional layers

CNNs in Keras

Keras for expression recognition

Optimizing the network

Summary

Exploiting Text Embedding

Machine learning for NLP

Understanding word embeddings

GloVe

Summary

Working with RNNs

Understanding RNNs

Long Short-Term Memory

LSTMs in Keras

Summary

Reusing Neural Networks with Transfer Learning

Transfer learning theory

Implementing MTL

Feature extraction

Implementing TL in PyTorch

Summary

Section 3: Advanced Applications

Working with Generative Algorithms

Discriminative versus generative algorithms

Understanding GANs

GAN variations and timelines

Recommendations for you

Python Machine Learning By Example

Jul 2024 518 pages

4.9 (8)

eBook

$9.99 ~~$36.99~~

Unlocking Data with Generative AI and RAG

Sep 2024 346 pages

eBook

$9.99 ~~$31.99~~

Building LLM Powered Applications

May 2024 342 pages

4.2 (22)

eBook

$9.99 ~~$39.99~~

Python for Algorithmic Trading Cookbook

Aug 2024 404 pages

4.6 (15)

eBook

$9.99 ~~$47.99~~

Machine Learning with PyTorch and Scikit-Learn

Feb 2022 774 pages

4.4 (95)

eBook

$9.99 ~~$43.99~~

Artificial Intelligence Engines

Nov 2024 217 pages

eBook

$6.98 ~~$9.99~~

AI Product Manager's Handbook

Nov 2024 484 pages

eBook

$9.99 ~~$39.99~~

RAG-Driven Generative AI

Sep 2024 334 pages

4.5 (13)

eBook

$9.99 ~~$35.99~~

Hands-On Reinforcement Learning with Python

Jun 2018 318 pages

2.6 (18)

eBook

$9.99 ~~$29.99~~

LLM Engineer's Handbook

Oct 2024 522 pages

4.8 (16)

eBook

$9.99 ~~$47.99~~

Customer reviews

Rating distribution

3.5

(2 Ratings)

5 star 50%

4 star 0%

3 star 0%

2 star 50%

1 star 0%

Al Oct 11, 2019

Excellent and comprehensive insight! I love the author's big picture view and how it translated it in simple python code.

Amazon Verified review

Saadallah Kassir Jan 12, 2021

- The topics discussed are interesting and useful, although some chapters need additional explanation. Some of the concepts are indeed discussed at a very high level.- The notation may be a bit hard to follow as variables are sometimes undefined. Some terminology is not technically correct, e.g., confusion between MSE and RMSE, with a confusing expression.- The code snippets may be confusing, as some instructions may be irrelevant, e.g., instructions defining variables that are never used.- The book is printed in grayscale, which makes it harder to read the figures, although the authors indicated that all the figures are available in color online.- Several typos/missing words make some paragraphs hard to read.Overall, I like the idea of the book, but it may be worth waiting for the issue of a new edition, as several errors may be confusing to the reader.

Amazon Verified review

People who bought this also bought

Machine Learning Engineering with Python

Aug 2023 462 pages

4.6 (36)

eBook

$9.99 ~~$39.99~~

Deep Learning with TensorFlow and Keras – 3rd edition

Oct 2022 698 pages

4.6 (45)

eBook

$9.99 ~~$39.99~~

Modern Generative AI with ChatGPT and OpenAI Models

May 2023 286 pages

4.2 (34)

eBook

$9.99 ~~$39.99~~

Generative AI with LangChain

Dec 2023 368 pages

4 (34)

eBook

$9.99 ~~$39.99~~

Causal Inference and Discovery in Python

May 2023 456 pages

4.5 (49)

eBook

$9.99 ~~$31.99~~

About the authors

Leonardo De Marchi

Leonardo De Marchi is an international speaker, author and consultant. He holds a masters in artificial intelligence (AI) and has worked as a data scientist in the sporting world, with clients such as New York Knicks, Manchester United. He now works as a head of data scientist at Badoo, the largest dating site with over 400 million users. He is also the lead instructor at ideai.io, a company specialized in Machine Learning trainings. With Ideai he provides technical and managerial training to large institutions and dynamic startups. He is also a contractor for the European Commission.

See other products by Leonardo De Marchi

Laura Mitchell

Laura Mitchell graduated with a degree in mathematics from the University of Edinburgh and, since then, has gained over 12 years' experience in the tech and data science space. She is currently lead data scientist at Badoo, which is the largest online dating site in the world with over 400 million users worldwide. Laura has hands-on experience in the delivery of projects such as NLP, image classification, and recommender systems, from initial conception through to production. She has a passion for learning new technologies and keeping up to date with industry trends.

See other products by Laura Mitchell

FAQs

What is included in a Packt subscription?

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription?

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits?

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled?

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title?

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team.

Can I download the code files for Early Access titles?

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date?

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready?

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access?

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered?

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content?

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access?

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.

Hands-On Neural Networks: Learn how to build and train your first neural network model using Python

What do you get with a Packt Subscription?