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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.
Book description · Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagation · See how DL frameworks make it ...
Learning Deep Learning: Theory and Practice of Neural Networks, Computer Vision, Natural Language Processing, and Transformers Using TensorFlow
Book by Magnus Ekman
NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results "To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards... Google Books
Originally published: July 19, 2021
Author: Magnus Ekman
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This chapter describes the concept of datasets and how they can be divided into a training set and a test set. It also touches on a network's ability to ...
When attempting to apply neural networks to real-world problems one is confronted with a major problem — there is no general theory about which network ...
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Jul 18, 2021 · Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, ...
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Learning Deep Learning: Theory and Practice of Neural Networks, Computer Vision, Natural Language Processing, and Transformers Using TensorFlow. by Magnus Ekman.
Learning Deep Learning. Theory and Practice of Neural Networks, Computer Vision, Natural Language Processing, and Transformers Using TensorFlow.
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He describes how these concepts are used to build modernnetworks for computer vision and natural language processing (NLP), includingMask R-CNN, GPT, ...
Sep 29, 2023 · The neural tangent kernel (NTK) has garnered significant attention as a theoretical framework for describing the behavior of large-scale neural networks.