Isbn: 9781718503922 - deep learning crash course (39 resultados)

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Paperback. Condición: new. Paperback. A complete guide to deep neural networks - the technology behind AI - covering fundamental and advanced techniques to apply machine learning in real-world scenarios.Build AI Models from Scratch (No PhD Required)Deep Learning Crash Course is a fast-paced, thorough introduction that will have you building today's most powerful AI models from scratch. No experience with deep learning required!Designed for programmers who may be new to deep learning, this book offers practical, hands-on experience, not just an abstract understanding of theory.You'll start from the basics, and using PyTorch with real datasets, you'll quickly progress from your first neural network to advanced architectures like convolutional neural networks (CNNs), transformers, diffusion models, and graph neural networks (GNNs). Each project can be run on your own hardware or in the cloud, with annotated code available on GitHub.You'll build and train models to:Classify and analyze images, sequences, and time seriesGenerate and transform data with autoencoders, GANs (generative adversarial networks), and diffusion modelsProcess natural language with recurrent neural networks and transformersModel molecules and physical systems with graph neural networksImprove continuously through reinforcement and active learningPredict chaotic systems with reservoir computingWhether you're an engineer, scientist, or professional developer, you'll gain fluency in deep learning and the confidence to apply it to ambitious, real-world problems. With Deep Learning Crash Course, you'll move from using AI tools to creating them. "A comprehensive, hands-on guide to deep learning using Python, combining theoretical concepts with practical examples and step-by-step code implementation. Covers foundational topics as well as advanced subjects such as generative models and reinforcement learning"-- Provided by publisher. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

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Paperback. Condición: New. Deep Learning Crash Course goes beyond the basics of machine learning to delve into modern techniques and applications of great interest right now, and whose popularity will only grow in the future. The book covers topics such as generative models (the technology behind deep fakes), self-supervised learning, attention mechanisms (the tech behind ChatGPT), graph neural networks (the tech behind AlphaFold), and deep reinforcement learning (the tech behind AlphaGo). This book bridges the gap between theory and practice, helping readers gain the confidence to apply deep learning in their work.…

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Paperback. Condición: Brand New. 472 pages. 9.25x7.00x9.25 inches. In Stock.

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Taschenbuch. Condición: Neu. Neuware -Build AI Models from Scratch (No PhD Required)Deep Learning Crash Course is a fast-paced, thorough introduction that will have you building today's most powerful AI models from scratch. No experience with deep learning required!Designed for programmers who may be new to deep learning, this book offers practical, hands-on experience, not just an abstract understanding of theory.You'll start from the basics, and using PyTorch with real datasets, you'll quickly progress from your first neural network to advanced architectures like convolutional neural networks (CNNs), transformers, diffusion models, and graph neural networks (GNNs). Each project can be run on your own hardware or in the cloud, with annotated code available on GitHub.You'll build and train models to: - Classify and analyze images, sequences, and time series- Generate and transform data with autoencoders, GANs (generative adversarial networks), and diffusion models- Process natural language with recurrent neural networks and transformers- Model molecules and physical systems with graph neural networks- Improve continuously through reinforcement and active learning- Predict chaotic systems with reservoir computingWhether you're an engineer, scientist, or professional developer, you'll gain fluency in deep learning and the confidence to apply it to ambitious, real-world problems. With Deep Learning Crash Course, you'll move from using AI tools to creating them. 680 pp. Englisch.…

Taschenbuch. Condición: Neu. Neuware -Build AI Models from Scratch (No PhD Required)Deep Learning Crash Course is a fast-paced, thorough introduction that will have you building today's most powerful AI models from scratch. No experience with deep learning required!Designed for programmers who may be new to deep learning, this book offers practical, hands-on experience, not just an abstract understanding of theory.You'll start from the basics, and using PyTorch with real datasets, you'll quickly progress from your first neural network to advanced architectures like convolutional neural networks (CNNs), transformers, diffusion models, and graph neural networks (GNNs). Each project can be run on your own hardware or in the cloud, with annotated code available on GitHub.You'll build and train models to: - Classify and analyze images, sequences, and time series- Generate and transform data with autoencoders, GANs (generative adversarial networks), and diffusion models- Process natural language with recurrent neural networks and transformers- Model molecules and physical systems with graph neural networks- Improve continuously through reinforcement and active learning- Predict chaotic systems with reservoir computingWhether you're an engineer, scientist, or professional developer, you'll gain fluency in deep learning and the confidence to apply it to ambitious, real-world problems. With Deep Learning Crash Course, you'll move from using AI tools to creating them. 680 pp. Englisch.…

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Paperback. Condición: new. Paperback. A complete guide to deep neural networks - the technology behind AI - covering fundamental and advanced techniques to apply machine learning in real-world scenarios.Build AI Models from Scratch (No PhD Required)Deep Learning Crash Course is a fast-paced, thorough introduction that will have you building today's most powerful AI models from scratch. No experience with deep learning required!Designed for programmers who may be new to deep learning, this book offers practical, hands-on experience, not just an abstract understanding of theory.You'll start from the basics, and using PyTorch with real datasets, you'll quickly progress from your first neural network to advanced architectures like convolutional neural networks (CNNs), transformers, diffusion models, and graph neural networks (GNNs). Each project can be run on your own hardware or in the cloud, with annotated code available on GitHub.You'll build and train models to:Classify and analyze images, sequences, and time seriesGenerate and transform data with autoencoders, GANs (generative adversarial networks), and diffusion modelsProcess natural language with recurrent neural networks and transformersModel molecules and physical systems with graph neural networksImprove continuously through reinforcement and active learningPredict chaotic systems with reservoir computingWhether you're an engineer, scientist, or professional developer, you'll gain fluency in deep learning and the confidence to apply it to ambitious, real-world problems. With Deep Learning Crash Course, you'll move from using AI tools to creating them. "A comprehensive, hands-on guide to deep learning using Python, combining theoretical concepts with practical examples and step-by-step code implementation. Covers foundational topics as well as advanced subjects such as generative models and reinforcement learning"-- Provided by publisher. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. …

Paperback. Condición: Brand New. 472 pages. 9.25x7.00x9.25 inches. In Stock.

Paperback. Condición: Brand New. 472 pages. 9.25x7.00x9.25 inches. In Stock.

Taschenbuch. Condición: Neu. Neuware -Build AI Models from Scratch (No PhD Required)Deep Learning Crash Course is a fast-paced, thorough introduction that will have you building today's most powerful AI models from scratch. No experience with deep learning required!Designed for programmers who may be new to deep learning, this book offers practical, hands-on experience, not just an abstract understanding of theory.You'll start from the basics, and using PyTorch with real datasets, you'll quickly progress from your first neural network to advanced architectures like convolutional neural networks (CNNs), transformers, diffusion models, and graph neural networks (GNNs). Each project can be run on your own hardware or in the cloud, with annotated code available on GitHub.You'll build and train models to: - Classify and analyze images, sequences, and time series- Generate and transform data with autoencoders, GANs (generative adversarial networks), and diffusion models- Process natural language with recurrent neural networks and transformers- Model molecules and physical systems with graph neural networks- Improve continuously through reinforcement and active learning- Predict chaotic systems with reservoir computingWhether you're an engineer, scientist, or professional developer, you'll gain fluency in deep learning and the confidence to apply it to ambitious, real-world problems. With Deep Learning Crash Course, you'll move from using AI tools to creating them.…

Paperback. Condición: New. Deep Learning Crash Course goes beyond the basics of machine learning to delve into modern techniques and applications of great interest right now, and whose popularity will only grow in the future. The book covers topics such as generative models (the technology behind deep fakes), self-supervised learning, attention mechanisms (the tech behind ChatGPT), graph neural networks (the tech behind AlphaFold), and deep reinforcement learning (the tech behind AlphaGo). This book bridges the gap between theory and practice, helping readers gain the confidence to apply deep learning in their work.…