Learning deep learning : theory and practice of neural networks, computer vision, nlp, and transformers using tensorflow / Magnus Ekman.
By: Ekman, Magnus [author.].
Publisher: Boston : Addison-Wesley, ©2022Edition: First edition.Description: 688 p.Content type: text Media type: unmediated Carrier type: volumeISBN: 9780137470358.Genre/Form: Print books.Summary: "Deep learning is at the heart of many of today's most exciting advances in machine learning and artificial intelligence. Pioneering applications at companies like Tesla, Google, and Facebook are now being followed by massive investments in fields ranging from finance to healthcare. Now, there's a complete guide to deep learning with TensorFlow, the #1 Python library for building these breakthrough applications. Magnus Ekman illuminates both the underlying concepts and the hands-on programming techniques you'll need, even if you have no machine learning experience. Throughout, you'll find concise, well-annotated code examples using TensorFlow and the Keras API; for comparison and easy migration between frameworks, complementary examples in PyTorch are provided online. Ekman also explains enough of the mathematics to help newcomers grasp how deep learning actually works. The guide concludes by previewing emerging trends in deep learning, and exploring the challenging ethical issues surrounding its use"--| Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|
| On Shelf | Q325.5 .E36 2022 (Browse shelf) | Available | AU00000000019453 |
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| Q325.5 .B87 2020 Machine learning engineering / | Q325.5 .C45 2018 Machine learning and security : protecting systems with data and algorithms / | Q325.5 .D45 2020 Mathematics for machine learning / | Q325.5 .E36 2022 Learning deep learning : theory and practice of neural networks, computer vision, nlp, and transformers using tensorflow / | Q325.5 .E87 2020 Introducing machine learning / | Q325.5 .F38 2020 A concise introduction to machine learning / | Q325.5 .F43 2018 Feature engineering for machine learning and data analytics / |
"Deep learning is at the heart of many of today's most exciting advances in machine learning and artificial intelligence. Pioneering applications at companies like Tesla, Google, and Facebook are now being followed by massive investments in fields ranging from finance to healthcare. Now, there's a complete guide to deep learning with TensorFlow, the #1 Python library for building these breakthrough applications. Magnus Ekman illuminates both the underlying concepts and the hands-on programming techniques you'll need, even if you have no machine learning experience. Throughout, you'll find concise, well-annotated code examples using TensorFlow and the Keras API; for comparison and easy migration between frameworks, complementary examples in PyTorch are provided online. Ekman also explains enough of the mathematics to help newcomers grasp how deep learning actually works. The guide concludes by previewing emerging trends in deep learning, and exploring the challenging ethical issues surrounding its use"--