Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Hands-On Neural Networks
  • Table Of Contents Toc
  • Feedback & Rating feedback
Hands-On Neural Networks

Hands-On Neural Networks

By : Leonardo De Marchi, Laura Mitchell
3.5 (2)
close
close
Hands-On Neural Networks

Hands-On Neural Networks

3.5 (2)
By: Leonardo De Marchi, Laura Mitchell

Overview of this book

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.
Table of Contents (16 chapters)
close
close
Lock Free Chapter
1
Section 1: Getting Started
4
Section 2: Deep Learning Applications
9
Section 3: Advanced Applications

Understanding word embeddings

Embedding is a mathematical structure contained within another instance. If we are embedding an object X in an object Y, we will be preserving the structure of the objects and so the instance.

Word embedding is a technique to map words to vectors, creating a multidimensional space that will allow the creation of similar representations for similar words. Each word is represented by a single vector with often tens or hundreds of dimensions, in contrast to other representations such as one-hot encoding that can have thousands or even millions of dimensions.

When we have words in the form of vectors, we end up using all mathematical techniques that we would on pure numbers. Also when transformed into vectors, words will keep the same proprieties that numbers have.

It also means that we could start doing operations as follows:

King - man + woman =queen...

Visually different images
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Hands-On Neural Networks
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon