000			02089nam a22002657a 4500
003			OSt
005			20260520130300.0
008			260520b |||||||| |||| 00| 0 eng d
020			_a9789365897388
041			_aeng
082			_a006.31 FOS-G
100			_aFoster, David _979309
245			_aGenerative deep learning : _bteaching machines to paint, write, compose, and play
250			_a2nd
260			_aMumbai _bSPD Shroff Publishers & Distributors Pvt. Ltd. _c2023
300			_axxvi, 426p.
520			_aGenerative AI is the hottest topic in tech. 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, normalising flows, energy-based models, and denoising diffusion models. The book starts with the basics of deep learning and progresses to cutting-edge architectures. Through tips and tricks, you'll understand how to make your models learn more efficiently and become more creative. Discover how VAEs can change facial expressions in photos Train GANs to generate images based on your own dataset Build diffusion models to produce new varieties of flowers Train your own GPT for text generation Learn how large language models like ChatGPT are trained Explore state-of-the-art architectures such as StyleGAN2 and ViT-VQGAN Compose polyphonic music using Transformers and MuseGAN Understand how generative world models can solve reinforcement learning tasks Dive into multimodal models such as DALL.E 2, Imagen, and Stable Diffusion This book also explores the future of generative AI and how individuals and companies can proactively leverage this remarkable new technology to gain a competitive advantage.
650			_aArtificial intelligence. _979310
650			_aGenerative AI. _979311
650			_aDeep learning _979312
650			_aMachine learning _979313
650			_aNeural networks _979314
942			_cBK
999			_c199992 _d199992