Название: Zefs Guide to Deep Learning (2023-05-31 Update)Автор: Roy Keyes
Издательство: Leanpub
Год: 2023-05-31
Страниц: 163
Язык: английский
Формат: pdf (true), epub
Размер: 25.0 MB
Zefs Guide to Deep Learning is a short guide to the most important concepts in Deep Learning, the technique at the center of the current Artificial Intelligence (AI) revolution. It will give you a strong understanding of the core ideas and most important methods and applications. All in around only 150 pages!
This book presents the foundational concepts behind Machine Learning, neural networks, and the recent major advancements in architectures and training techniques in an easy to understand way. It also covers the most important applications of deep neural networks, including Computer Vision, natural language processing (NLP}, and beyond. Your time is valuable, Zefs Guide to Deep Learning will get you up to speed in around only 163 pages!
This book is about Deep Learning, a set of Machine Learning methods that have sparked a huge amount of interest in applying computational and predictive models to everything from whimsical face filters to medical imaging to generating computer code itself. Deep learning is at the core of the current “AI revolution”. While based on techniques that can be traced back more than half a century, only in the past decade have these techniques really come into their own and they now dominate the predictive modeling space for an increasingly large number of use cases. This book aims to help you get a better high-level, conceptual understanding of how Deep Learning works, its central concepts, applications, limitations, and possibilities.
Machine Learning (ML) is an approach to solving problems, where data is used directly to adjust the internal parameters of a computer program to provide the best answers possible. Examples include predicting the ultimate sale price of a house or detecting the presence of a tumor in a medical scan. The difference between machine learning programs (usually called “models”) and traditional computer programs is that instead of having programmers explicitly write the logic of the program by hand, the important decision logic is “learned” by the program by looking at example data. This process is called training the model.
This book covers the concepts behind neural networks and deep learning, the key ideas you need to understand to build deep neural networks for solving problems, the common network architectures, and the common use cases that are solved with deep learning. It is, however, not exhaustive. Zefs Guide to Deep Learning is the first in a series of books on Deep Learning topics from Zefs Guides. The current plan for the series includes the titles Zefs Guide to Computer Vision, Zefs Guide to Natural Language Processing, and Zefs Guide to Transformers. Those books all build on the concepts contained in this book.
Why deep learning?
Deep Learning is a name applied to a class of neural networks with many “layers”, allowing them to be trained to perform certain kinds of tasks that traditional modeling techniques have not been able to do nearly as well. In some cases these deep neural networks can even outperform humans on these tasks, which has fueled the high level of excitement around this family of methods.
Contents:
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