Harness the power of AI with this guide to using Keras! Start by reviewing the fundamentals of deep learning and installing the Keras API. Next, follow Python code examples to build your own models, and then train them using classification, gradient descent, and regularization. Design large-scale, multilayer models and improve their decision making with reinforcement learning. With tips for creating generative AI models, this is your cutting-edge resource for working with deep learning!
Highlights include:
1)Neural networks
2)Gradient descent
3)Classification
4)Regularization
5)Convolutional neural networks (CNNs)
6)Functional API
7)Transformer architecture
8)Reinforcement learning
9)Autoencoders
10)Stable Diffusion
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Dr. Mohammad Nauman is a seasoned machine learning expert with more than 20 years of teaching experience and a track record of educating 40,000+ students globally through his paid and free online courses on platforms like Udemy and YouTube. He has a post-doctorate degree from Max Planck Institute for Software Systems, Germany. He holds a PhD in computer science, with his groundbreaking work at the Max Planck Institute focusing on applying machine learning to advance security and privacy solutions. Dr. Nauman’s teaching philosophy―rooted in bridging theory and practice―empowers learners to master tools while building robust foundational skills, whether in academic settings or through his widely accessible digital programs.
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Paperback. Zustand: new. Paperback. Harness the power of AI with this guide to using Keras! Start by reviewing the fundamentals of deep learning and installing the Keras API. Next, follow Python code examples to build your own models, and then train them using classification, gradient descent, and regularization. Design large-scale, multilayer models and improve their decision making with reinforcement learning. With tips for creating generative AI models, this is your cutting-edge resource for working with deep learning!Highlights include: 1) Neural networks2) Gradient descent3) Classification4) Regularization5) Convolutional neural networks (CNNs)6) Functional API7) Transformer architecture8) Reinforcement learning9) Autoencoders10) Stable Diffusion Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781493227396
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