Python Deep Learning
Valentino Zocca, Gianmario Spacagna, Daniel Slater, Peter Roelants
Idioma: inglés
Editorial: Packt Publishing Limited, GB, 2023
- Tapa blanda
- Nuevo
Librería: Rarewaves.com USA, London, London, Reino UnidoRarewaves.com USA
Vendedor de IberLibro desde 11 de junio de 2025
Condición: Nuevo
EUR 75,46
Cantidad disponible: Más de 20 disponibles
Añadir al carritoDescripción del artículo del vendedor
Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.About This Book. Explore and create intelligent systems using cutting-edge deep learning techniques. Implement deep learning algorithms and work with revolutionary libraries in Python. Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and moreWho This Book Is ForThis book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired.What You Will Learn. Get a practical deep dive into deep learning algorithms. Explore deep learning further with Theano, Caffe, Keras, and TensorFlow. Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines. Dive into Deep Belief Nets and Deep Neural Networks. Discover more deep learning algorithms with Dropout and Convolutional Neural Networks. Get to know device strategies so you can use deep learning algorithms and libraries in the real worldIn DetailWith an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries.The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results.Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques.Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside.Style and approachPython Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects.…
N° de ref. del artículo LU-9781786464453
- Título
- Python Deep Learning
- Autor
- Valentino Zocca, Gianmario Spacagna, Daniel Slater, Peter Roelants
- Editorial
- Packt Publishing Limited, GB
- Año de publicación
- 2023
- Estado
- New
- Encuadernación
- Digital
- Idioma
- inglés
- ISBN 10
- 1786464454
- ISBN 13
- 9781786464453
- Peso del artículo
- 694 gramos
- Dimensiones
- 19.05 x 2.34 x 23.5 cm
Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.
Key Features:
- Explore and create intelligent systems using cutting-edge deep learning techniques
- Implement deep learning algorithms and work with revolutionary libraries in Python
- Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and more
Book Description:
With an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries.
The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results.
Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques.
Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside.
What You Will Learn:
- Get a practical deep dive into deep learning algorithms
- Explore deep learning further with Theano, Caffe, Keras, and TensorFlow
- Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines
- Dive into Deep Belief Nets and Deep Neural Networks
- Discover more deep learning algorithms with Dropout and Convolutional Neural Networks
- Get to know device strategies so you can use deep learning algorithms and libraries in the real world
Who this book is for:
This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired.
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
Daniel Slater started programming at age 11, developing mods for the id Software game Quake. His obsession led him to become a developer working in the gaming industry on the hit computer game series Championship Manager. He then moved into finance, working on risk- and high-performance messaging systems. He now is a staff engineer working on big data at Skimlinks to understand online user behavior. He spends his spare time training AI to beat computer games. He talks at tech conferences about deep learning and reinforcement learning; and the name of his blog is Daniel Slater's blog. His work in this field has been cited by Google.
Valentino Zocca has a PhD degree and graduated with a Laurea in mathematics from the University of Maryland, USA, and University of Rome, respectively, and spent a semester at the University of Warwick. He started working on high-tech projects of an advanced stereo 3D Earth visualization software with head tracking at Autometric, a company later bought by Boeing. There he developed many mathematical algorithms and predictive models, and using Hadoop he automated several satellite-imagery visualization programs. He has worked as an independent consultant at the U.S. Census Bureau, in the USA and in Italy. Currently, Valentino lives in New York and works as an independent consultant to a large financial company.
“Acerca de” puede pertenecer a otra edición de este título.
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Vendedor de IberLibro desde 11 de junio de 2025
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