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ASIN : B08H185K3J
Publisher : The MIT Press (February 19, 2019)
Publication date : February 19, 2019
Language : English
File size : 5737 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 192 pages
Customers say
Customers find the book provides an accessible introduction to deep learning with enough detail to get started and practical advice on building real neural networks. However, opinions differ on the writing quality – some find it well-written, concise, and clear, while others feel it’s poorly written without much thought and has convoluted grammar.
AI-generated from the text of customer reviews
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Deep learning is a subset of artificial intelligence that focuses on training computers to learn and make decisions in a way that mimics the human brain. It involves using neural networks, which are algorithms that are inspired by the way neurons in the brain work.
In deep learning, these neural networks are trained on large amounts of data to recognize patterns and make predictions. This allows computers to perform tasks such as image and speech recognition, natural language processing, and autonomous driving.
One of the key features of deep learning is its ability to learn from data without being explicitly programmed. This means that as more data is fed into the system, the algorithms can continuously improve their performance and accuracy.
Deep learning has applications in a wide range of industries, including healthcare, finance, marketing, and more. It is revolutionizing the way we approach complex problems and is at the forefront of technological advancements.
In this post, we will explore the basic concepts of deep learning, the different types of neural networks, and some common applications of this powerful technology. Stay tuned to learn more about this exciting field!
#Introduction #Deep #Learning
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