How can I learn deep learning?
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To learn deep learning, it is important to become familiarized with the basic concepts and principles. Deep learning involves creating high level abstractions from data using large neural networks. It encompasses new concepts and methods beyond just neural networks. Start by revising some works relating to physics and deep learning . Then, learn about the main elements, their use, and several possible network architectures . Familiarity with linear algebra, multivariate calculus, and probability and statistics is required . Additionally, gaining practical experience by working through programs in machine learning frameworks like Tensorflow is beneficial . Deep Learning by Goodfellow, Bengio, and Courville is a comprehensive resource that covers mathematical and conceptual background, deep learning techniques, and applications . The Science of Deep Learning by Tang is another resource that covers the foundations of deep learning and key architectures .
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| You can learn deep learning by studying relevant concepts in mathematics, probability theory, and machine learning, and by practicing with deep learning techniques and applications. | |
| You can learn deep learning by working through programs in Tensorflow and completing programming projects in areas such as computer vision and natural language processing. | |
5 Citations | To learn deep learning, it is important to become familiar with the basic concepts and principles, as well as the main models and network architectures. |
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