Price: $59.99 – $51.62
(as of Dec 01,2024 10:50:35 UTC – Details)
Publisher : Manning; Annotated edition (May 31, 2022)
Language : English
Paperback : 600 pages
ISBN-10 : 1617298638
ISBN-13 : 978-1617298639
Item Weight : 2 pounds
Dimensions : 7.38 x 1.6 x 9.25 inches
Deep learning is a powerful subset of artificial intelligence that has revolutionized the way we approach complex problems in various fields such as computer vision, natural language processing, and autonomous vehicles. At its core, deep learning involves the use of mathematical concepts, algorithms, and models to train computers to make decisions and predictions.
Mathematics plays a crucial role in deep learning, as it provides the foundation for understanding how neural networks function and how they can be optimized for better performance. Concepts such as linear algebra, calculus, and probability theory are essential for developing and training deep learning models.
Algorithms are another key component of deep learning, as they dictate how data is processed and how neural networks learn from it. Popular algorithms such as backpropagation, stochastic gradient descent, and convolutional neural networks are widely used in deep learning applications to improve model accuracy and efficiency.
Deep learning models, such as deep neural networks and recurrent neural networks, are designed to mimic the structure and function of the human brain, allowing computers to learn from vast amounts of data and make intelligent decisions. These models are trained using labeled datasets to recognize patterns and make predictions based on new, unseen data.
In conclusion, deep learning is a complex and fascinating field that relies on a combination of mathematics, algorithms, and models to push the boundaries of artificial intelligence. By understanding the inner workings of deep learning, we can harness its potential to solve a wide range of real-world problems and drive innovation in various industries.
#Deep #Learning #Math #Algorithms #Models
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