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"This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch, including variational autoencoders (VAEs), generative adversarial networks (GANs), transformers, normalizing flows, energy-based models, and denoising diffusion models ... [and] also explores the future of generative AI and how individuals and companies can proactively begin to leverage this remarkable new technology to create competitive advantage"--
About the author
David Foster is a data scientist, entrepreneur, and educator specializing in AI applications within creative domains. As cofounder of Applied Data Science Partners (ADSP), he inspires and empowers organizations to harness the transformative power of data and AI. He holds an MA in Mathematics from Trinity College, Cambridge, an MSc in Operational Research from the University of Warwick, and is a faculty member of the Machine Learning Institute, with a focus on the practical applications of AI and real-world problem solving. His research interests include enhancing the transparency and interpretability of AI algorithms, and he has published literature on explainable machine learning within healthcare.
