Learning Deep Learning Theory and Practice of Neural Networks, Computer Vision, Natural Language Processing, and Transformers Using TensorFlow
Afbeeldingen
Artikel vergelijken
- Engels
- Paperback
- 9780137470358
- 11 oktober 2021
- 752 pagina's
Samenvatting
NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results
-- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA
"Ekman uses a learning technique that in our experience has proven pivotal to success—asking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us."
-- From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning Institute
Deep learning (DL) is a key component of today's exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience.
After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images.
Throughout, Ekman provides concise, well-annotated code examples using TensorFlow with Keras. Corresponding PyTorch examples are provided online, and the book thereby covers the two dominating Python libraries for DL used in industry and academia. He concludes with an introduction to neural architecture search (NAS), exploring important ethical issues and providing resources for further learning.
- Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagation
- See how DL frameworks make it easier to develop more complicated and useful neural networks
- Discover how convolutional neural networks (CNNs) revolutionize image classification and analysis
- Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences
- Master NLP with sequence-to-sequence networks and the Transformer architecture
- Build applications for natural language translation and image captioning
NVIDIA's invention of the GPU sparked the PC gaming market. The company's pioneering work in accelerated computing--a supercharged form of computing at the intersection of computer graphics, high-performance computing, and AI--is reshaping trillion-dollar industries, such as transportation, healthcare, and manufacturing, and fueling the growth of many others.
Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Productspecificaties
Inhoud
- Taal
- en
- Bindwijze
- Paperback
- Oorspronkelijke releasedatum
- 11 oktober 2021
- Aantal pagina's
- 752
Betrokkenen
- Hoofdauteur
- Magnus Ekman
- Hoofduitgeverij
- Addison Wesley
Overige kenmerken
- Product breedte
- 188 mm
- Product hoogte
- 32 mm
- Product lengte
- 230 mm
- Studieboek
- Ja
- Verpakking breedte
- 185 mm
- Verpakking hoogte
- 31 mm
- Verpakking lengte
- 223 mm
- Verpakkingsgewicht
- 1064 g
EAN
- EAN
- 9780137470358
Je vindt dit artikel in
- Categorieën
- Taal
- Engels
- Beschikbaarheid
- Leverbaar
- Boek, ebook of luisterboek?
- Boek
- Studieboek of algemeen
- Studieboeken
Kies gewenste uitvoering
Prijsinformatie en bestellen
De prijs van dit product is 44 euro en 99 cent.- Prijs inclusief verzendkosten, verstuurd door bol
- Ophalen bij een bol afhaalpunt mogelijk
- 30 dagen bedenktijd en gratis retourneren
- Dag en nacht klantenservice
Rapporteer dit artikel
Je wilt melding doen van illegale inhoud over dit artikel:
- Ik wil melding doen als klant
- Ik wil melding doen als autoriteit of trusted flagger
- Ik wil melding doen als partner
- Ik wil melding doen als merkhouder
Geen klant, autoriteit, trusted flagger, merkhouder of partner? Gebruik dan onderstaande link om melding te doen.