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Access through your institution Buy or subscribe UNDERSTANDING DEEP LEARNING * _Simon J. D. Prince_ The MIT Press: 2023. 544 pp. $90.00 The field of artificial intelligence (AI) has
experienced a surge in developments over the past years, propelled by breakthroughs in deep learning with neural networks. This has revolutionized many aspects of society. However, the speed
at which AI is advancing highlights the need for textbooks that provide essential resources for educating young researchers and professionals with the latest methodologies and best
practices in deep learning, guiding them in exploring uncharted territories and harnessing the full potential of AI. This is a preview of subscription content, access via your institution
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subscriptions * Read our FAQs * Contact customer support REFERENCES * Prince, J. D. S. _Understanding Deep Learning_ (MIT Press, 2024); https://udlbook.github.io/udlbook/ * Goodfellow, I.,
Bengio, Y. & Courville, A. _Deep Learning_ (MIT Press, 2016); https://www.deeplearningbook.org/ * Géron, A. _Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts,
Tools, and Techniques to Build Intelligent Systems_ edn 2 (O’Reilly, 2019). * Nielsen, M. _Neural Networks and Deep Learning_ 2nd edn (Springer, 2013);
https://www.goodreads.com/book/show/24582662-neural-networks-and-deep-learning * Shanmugamani, R. _Deep Learning for Computer Vision: Expert Techniques to Train Advanced Neural Networks
Using TensorFlow and Keras_ (Packt Publishing, 2018). * Bishop, C. M. & Bishop, H. _Deep Learning: Foundations and Concepts_ 1st edn (Springer, 2024). * Xu, Y. et al. _Adv. Neural Inf.
Process. Syst._ 35, 16782–16795 (2022). Download references AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of Biomedical Engineering, School of Engineering, Biomedical Imaging
Center, Center for Computational Innovations, Center for Biotechnology & Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, USA Ge Wang Authors * Ge Wang View author
publications You can also search for this author inPubMed Google Scholar CORRESPONDING AUTHOR Correspondence to Ge Wang. ETHICS DECLARATIONS COMPETING INTERESTS The author declares no
competing interests. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Wang, G. Diving into deep learning. _Nat Mach Intell_ 6, 502–503 (2024).
https://doi.org/10.1038/s42256-024-00840-8 Download citation * Published: 10 May 2024 * Issue Date: May 2024 * DOI: https://doi.org/10.1038/s42256-024-00840-8 SHARE THIS ARTICLE Anyone you
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