Deep Learning: Foundations and Concepts
Price: $89.99 - $78.22
(as of Nov 21,2024 14:40:58 UTC – Details)
Publisher : Springer; 2024th edition (November 2, 2023)
Language : English
Hardcover : 669 pages
ISBN-10 : 3031454677
ISBN-13 : 978-3031454677
Item Weight : 3.1 pounds
Dimensions : 7.75 x 1.5 x 10.5 inches
Customers say
Customers find the book a great technical reference for applied deep learning. They say it explains concepts well and is an excellent introduction to anyone wanting to learn about deep learning practices. Readers also appreciate the effort put into the wording, saying it’s easy to understand and succinct.
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Deep Learning: Foundations and Concepts
Deep learning is a subset of machine learning that uses artificial neural networks to model and solve complex problems. It has revolutionized the field of artificial intelligence and has led to significant advancements in areas such as computer vision, natural language processing, and speech recognition.
The foundations of deep learning lie in the concept of neural networks, which are computational models inspired by the structure and function of the human brain. These networks consist of layers of interconnected nodes, or neurons, that process and transform input data to produce output predictions.
Key concepts in deep learning include:
1. Neural network architecture: The structure of a neural network, including the number of layers, the number of neurons in each layer, and the connections between neurons.
2. Activation functions: Functions that introduce non-linearity into the network, allowing it to learn complex patterns and relationships in the data.
3. Loss functions: Functions that measure the difference between the predicted output of the network and the actual output, providing a measure of how well the network is performing.
4. Backpropagation: An algorithm used to update the weights of the network based on the error calculated by the loss function, allowing the network to learn from its mistakes and improve its predictions.
By understanding these foundational concepts and principles, practitioners can build and train deep learning models to tackle a wide range of tasks and challenges. Deep learning has the potential to transform industries and society as a whole, paving the way for more intelligent and efficient systems.
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