Practical Deep Learning, 2nd Edition: A Python-Based Introduction
Idioma: inglés
Editorial: No Starch Press,US, 2025
- Tapa blanda
- Usado
Librería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de AmericaWorld of Books (was SecondSale)
Vendedor de IberLibro desde 20 de diciembre de 2007
Condición: Usado - Bueno
EUR 25,02
Cantidad disponible: 2 disponibles
Añadir al carritoDescripción del artículo del vendedor
If you've been curious about artificial intelligence and machine learning but didn't know where to start, this is the book you've been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning, 2nd Edition teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math - the book will cover the rest. After an introduction to Python, you'll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models' performance. You'll also learn: How to use classic machine learning models like k-Nearest Neighbours, Random Forests, and Support Vector Machines, How neural networks work and how they're trained, How to use convolutional neural networks, How to develop a successful deep learning model from scratch. You'll conduct experiments along the way, building to a final case study that incorporates everything you've learned. This second edition is thoroughly revised and updated, and adds six new chapters to further your exploration of deep learning from basic CNNs to more advanced models. New chapters cover fine tuning, transfer learning, object detection, semantic segmentation, multilabel classification, self-supervised learning, generative adversarial networks, and large language models. The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning, 2nd Edition will give you the skills and confidence to dive into your own machine learning projects.…
N° de ref. del artículo 00108399940
- Título
- Practical Deep Learning, 2nd Edition: A Python-Based Introduction
- Autor
- Ronald T Kneusel
- Editorial
- No Starch Press,US
- Año de publicación
- 2025
- Estado
- Very Good
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 10
- 1718504209
- ISBN 13
- 9781718504202
- Edición
- 2ª Edición
If you’ve been curious about artificial intelligence and machine learning but didn’t know where to start, this is the book you’ve been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning, 2nd Edition teaches you the why of deep learning and will inspire you to explore further.
All you need is basic familiarity with computer programming and high school math—the book will cover the rest. After an introduction to Python, you’ll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models’ performance.
You’ll also learn:
- How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector Machines
- How neural networks work and how they’re trained
- How to use convolutional neural networks
- How to develop a successful deep learning model from scratch
You’ll conduct experiments along the way, building to a final case study that incorporates everything you’ve learned.
This second edition is thoroughly revised and updated, and adds six new chapters to further your exploration of deep learning from basic CNNs to more advanced models. New chapters cover fine tuning, transfer learning, object detection, semantic segmentation, multilabel classification, self-supervised learning, generative adversarial networks, and large language models.
The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning, 2nd Edition will give you the skills and confidence to dive into your own machine learning projects.
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
Ron's Ph.D. in computer science is from the University of Colorado, Boulder (2016). Ron also holds a master's degree in physics from Michigan State University and an undergraduate degree in physics and mathematics from Valparaiso University. Exactly when those particular degrees were awarded has been lost to the ages, but it was some time in the latter decades of the 20th century.
Ron's interests vary greatly but always orbit science, math, and technology. A child of the personal computer revolution in the late 1970s and early 1980s, Ron has been coding for longer than he's been able to drive. And, remarkably, it remains as fresh an enterprise now as it was all those decades ago.
“Acerca de” puede pertenecer a otra edición de este título.
World of Books (was SecondSale)
Montgomery, IL, Estados Unidos de America
Vendedor de IberLibro desde 20 de diciembre de 2007
Tarifas de envío en Estados Unidos de America
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