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Looking for a comprehensive guide to the exciting world of deep learning? Look no further than this must-have book! Written by a team of experts, this guide offers a deep dive into the world of artificial intelligence and machine learning. With clear explanations and practical examples, you'll learn how to use deep learning techniques to build powerful and innovative models that can solve complex problems. Whether you're a beginner or an experienced practitioner, this book has something for everyone. You'll learn the basics of neural networks, convolutional networks, and recurrent networks,…mehr

Produktbeschreibung
Looking for a comprehensive guide to the exciting world of deep learning? Look no further than this must-have book! Written by a team of experts, this guide offers a deep dive into the world of artificial intelligence and machine learning. With clear explanations and practical examples, you'll learn how to use deep learning techniques to build powerful and innovative models that can solve complex problems. Whether you're a beginner or an experienced practitioner, this book has something for everyone. You'll learn the basics of neural networks, convolutional networks, and recurrent networks, and discover how to use them to build image recognition systems, natural language processing models, and more. With easy-to-follow code samples and real-world case studies, you'll see how deep learning is revolutionizing industries from healthcare to finance. So if you're ready to take your machine learning skills to the next level, don't wait any longer. Get your hands on this essential guide to deep learning today!
Autorenporträt
Ian Goodfellow is a Research Scientist at Google. Yoshua Bengio is Professor of Computer Science at the Université de Montréal. Aaron Courville is Assistant Professor of Computer Science at the Université de Montréal.
Rezensionen
[T]he AI bible... the text should be mandatory reading by all data scientists and machine learning practitioners to get a proper foothold in this rapidly growing area of next-gen technology. Daniel D. Gutierrez, insideBIGDATA