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Python Advanced Guide Artificial by Bonaccorso Giuseppe (15 results)
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Python Advanced Guide to Artificial Intelligence: Advanced Guide to Artificial Intelligence: Expert machine learning systems and intelligent agents us (Paperback or Softback)
Published by Packt Publishing 12/12/2018, 2018
ISBN 10: 1789957214 ISBN 13: 9781789957211
Language: English
Paperback or Softback. Condition: New. Python Advanced Guide to Artificial Intelligence: Advanced Guide to Artificial Intelligence: Expert machine learning systems and intelligent agents us 2.84. Book.
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Python Advanced Guide to Artificial Intelligence: Advanced Guide to Artificial Intelligence: Expert machine learning systems and intelligent agents us
Published by Packt Publishing 2018-12, 2018
ISBN 10: 1789957214 ISBN 13: 9781789957211
Language: English
£ 42.03
Convert currency£ 15.49 shipping from United Kingdom to U.S.A.Quantity: 10 available
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Python: Advanced Guide to Artificial Intelligence: Expert machine learning systems and intelligent agents using Python
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Python: Advanced Guide to Artificial Intelligence
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Python: Advanced Guide to Artificial Intelligence
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PYTHON ADVANCED GUIDE TO ARTIFICIAL INTELLIGENCE: ADVANCED GUIDE TO ARTIFICIAL INTELLIGENCE: EXPERT
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Python Advanced Guide to Artificial Intelligence Expert machine learning systems and intelligent agents using Python
Published by Packt Publishing Limited, 2018
ISBN 10: 1789957214 ISBN 13: 9781789957211
Language: English
PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Python Advanced Guide to Artificial Intelligence Expert machine learning systems and intelligent agents using Python
Published by Packt Publishing Limited, 2018
ISBN 10: 1789957214 ISBN 13: 9781789957211
Language: English
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 4 out of 5 stars
£ 45.52
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Python: Advanced Guide to Artificial Intelligence
Published by Packt Publishing, Limited, 2018
ISBN 10: 1789957214 ISBN 13: 9781789957211
Language: English
£ 59.13
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key Features:Master supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image classification, similarity learning, and more Build, deploy, and scale end-to-end deep neural network models in a production environment Book Description: This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems This Learning Path includes content from the following Packt products: ¿ Mastering Machine Learning Algorithms by Giuseppe Bonaccorso ¿ Mastering TensorFlow 1.x by Armando Fandango ¿ Deep Learning for Computer Vision by Rajalingappaa Shanmugamani What you will learn:Explore how an ML model can be trained, optimized, and evaluated Work with Autoencoders and Generative Adversarial Networks Explore the most important Reinforcement Learning techniques Build end-to-end deep learning (CNN, RNN, and Autoencoders) models Who this book is for: This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some understanding of machine learning concepts are required to get the best out of this Learning Path.
