| INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781839219535 |
| DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Call number |
005.133 AR AR |
| MAIN ENTRY--PERSONAL NAME |
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| Authors |
Artasanchez, Alberto |
| TITLE STATEMENT |
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| Title |
Artificial Intelligence with Python : |
| Subtitle |
your complete guide to building intelligent apps using Python 3.x |
| Statement of responsibility, etc |
Alberto Artasanchez, Prateek Joshi |
| VARYING FORM OF TITLE |
|---|
| Title proper/short title |
your complete guide to building intelligent apps using Python three x |
| VARYING FORM OF TITLE |
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| Title proper/short title |
Mastering qlik sense : expert techniques on self-service data analytics to create enterprise ready business intelligence solutions |
| EDITION STATEMENT |
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| Edition |
2nd ed. |
| PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Place of publication |
Birmingham : |
| Publisher |
Packt Publishing, |
| Date |
c2020. |
| PHYSICAL DESCRIPTION |
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| Extent |
xviii, 592 p. : |
| Other Details |
ill. ; |
| Size |
24 cm. |
| SERIES STATEMENT |
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| Series statement |
Expert insight |
| CONTENTS |
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| Contents |
Table of ContentsIntroduction to Artificial IntelligenceFundamental Use Cases for Artificial IntelligenceMachine Learning PipelinesFeature Selection and Feature EngineeringClassification and Regression Using Supervised LearningPredictive Analytics with Ensemble LearningDetecting Patterns with Unsupervised LearningBuilding Recommender SystemsLogic ProgrammingHeuristic Search TechniquesGenetic Algorithms and Genetic ProgrammingArtificial Intelligence on the CloudBuilding Games with Artificial IntelligenceBuilding a Speech RecognizerNatural Language ProcessingChatbotsSequential Data and Time Series AnalysisImage RecognitionNeural NetworksDeep Learning with Convolutional Neural NetworksRecurrent Neural Networks and Other Deep Learning ModelsCreating Intelligent Agents with Reinforcement LearningArtificial Intelligence and Big Data |
| SUMMARY |
|---|
| Summary |
New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x and TensorFlow 2, with seven new chapters that cover RNNs, AI & Big Data, fundamental use cases, chatbots, and more. Key Features Completely updated and revised to Python 3.x and TensorFlow 2 New chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineering Learn more about deep learning algorithms, machine learning data pipelines, and chatbots Book Description Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x and TensorFlow 2. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques. What you will learn Understand what artificial intelligence, machine learning, and data science are Explore the most common artificial intelligence use cases Learn how to build a machine learning pipeline Assimilate the basics of feature selection and feature engineering Identify the differences between supervised and unsupervised learning Discover the most recent advances and tools offered for AI development in the cloud Develop automatic speech recognition systems and chatbots Apply AI algorithms to time series data Who this book is for The intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory. |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical Heading |
Python (Computer program language) |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical Heading |
Artificial intelligence |
| General |
Data processing |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical Heading |
Application software |
| General |
Development |
| ADDED ENTRY |
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| Name |
Joshi, Prateek |
| ADDED ENTRY |
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| Name |
Mahler, Martin |
| ADDED ENTRY |
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| Name |
Vitantonio, Juan Ignacio |
| ELECTRONIC LOCATION AND ACCESS |
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| Uniform Resource Identifier |
https://uowd.box.com/s/mskb7tbhnm3pugaj7r20iupspc28xd9n |
| Public note |
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