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Publisher ‏ : ‎ The MIT Press (December 5, 2023)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 544 pages
ISBN-10 ‏ : ‎ 0262048647
ISBN-13 ‏ : ‎ 978-0262048644
Item Weight ‏ : ‎ 2.95 pounds
Dimensions ‏ : ‎ 8.25 x 1.44 x 9.31 inches

Deep learning is a subset of machine learning that uses artificial neural networks to model and solve complex problems. It is a type of machine learning that is inspired by the structure and function of the human brain. Deep learning algorithms attempt to learn and understand the underlying structure of data by using multiple layers of interconnected nodes, known as neurons.

One of the key advantages of deep learning is its ability to automatically learn representations of data through a hierarchical feature learning process. This means that deep learning models can automatically extract and learn relevant features from raw data, without the need for manual feature engineering.

Deep learning has been successfully applied to a wide range of tasks, including image and speech recognition, natural language processing, and autonomous driving. By leveraging the power of neural networks and large amounts of data, deep learning has achieved state-of-the-art performance on many challenging problems.

To understand deep learning, it is important to have a basic understanding of neural networks, backpropagation, and optimization algorithms such as gradient descent. Additionally, knowledge of programming languages such as Python and libraries like TensorFlow and PyTorch is essential for implementing deep learning models.

Overall, deep learning offers a powerful framework for solving complex problems and has the potential to revolutionize many industries in the years to come. By understanding the principles and techniques of deep learning, practitioners can harness its full potential and unlock new possibilities in artificial intelligence and machine learning.
#Understanding #Deep #Learning