Isbn: 9781718500747 - practical deep learning: a python-based introduction (40 risultati)

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Paperback. Condizione: new. Paperback. Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects.Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects.If you've been curious about artificial intelligence and machine learning but didn't know where to start, this is the book you've been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further.All you need is basic familiarity with computer programming and high school math-the book will cover the rest. After an introduction to Python, you'll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models' performance.You'll also learn:How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector MachinesHow neural networks work and how they're trainedHow to use convolutional neural networksHow to develop a successful deep learning model from scratchYou'll conduct experiments along the way, building to a final case study that incorporates everything you've learned.The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning will give you the skills and confidence to dive into your own machine learning projects. A book for people with no experience with machine learning and who are looking for an intuition-based, hands-on introduction using Python. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Paperback. Condizione: New. Deep Learning for Complete Beginners: A Python-Based Introduction is for complete beginners in machine learning. It introduces fundamental concepts such as classes and labels, building a dataset, and what a model is and does before presenting classic machine learning models, neural networks, and modern convolutional neural networks. Experiments in Python - working with leading open-source toolkits and standard datasets - give the reader hands-on experience with each model and help them build intuition about how to transfer the examples in the book to their own projects.…

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Condizione: New. pp. 450.

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Condizione: New. 2021. Paperback. . . . . .

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Condizione: New. pp. 450.

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Taschenbuch. Condizione: Neu. Neuware -Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects.If you ve been curious about artificial intelligence and machine learning but didn t know where to start, this is the book you ve been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further.All you need is basic familiarity with computer programming and high school math the book will cover the rest. After an introduction to Python, you ll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models performance.You ll also learn:How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector MachinesHow neural networks work and how they re trainedHow to use convolutional neural networksHow to develop a successful deep learning model from scratchYou ll conduct experiments along the way, building to a final case study that incorporates everything you ve learned.The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning will give you the skills and confidence to dive into your own machine learning projects. Englisch.…

Taschenbuch. Condizione: Neu. Neuware -Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects.If you ve been curious about artificial intelligence and machine learning but didn t know where to start, this is the book you ve been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further.All you need is basic familiarity with computer programming and high school math the book will cover the rest. After an introduction to Python, you ll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models performance.You ll also learn:How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector MachinesHow neural networks work and how they re trainedHow to use convolutional neural networksHow to develop a successful deep learning model from scratchYou ll conduct experiments along the way, building to a final case study that incorporates everything you ve learned.The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning will give you the skills and confidence to dive into your own machine learning projects. Englisch.…

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