A Textbook
by Charu C. Aggarwal
appears in Machine Learning.
This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural Architecture,s in different applicatio...
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Why recommended
appears in Machine Learning.
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Consider Deep Learning by Ian Goodfellow. Recommended by 10 sources.
“Equation-forward introduction covering probability, linear-algebra foundations, optimization methods, model families, and common architectures. Sections trade short conceptual summaries for formal derivations and algorithm descriptions; occasional practical notes appear but runnable code is rare. Most useful for building a technical picture of why methods behave as they do and for informed follow-up experimentation. Main limitation: dense notation and extended proofs demand slow, focused study, so readers seeking hands-on walkthroughs will be left wanting.”
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