ISBN: 9780135224335 - python for programmers: with introductory ai case studies (45 risultati)

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Paperback. Condizione: New. The professional programmer's Deitel® guide to Python® with introductory artificial intelligence case studies Written for programmers with a background in another high-level language, Python for Programmers uses hands-on instruction to teach today's most compelling, leading-edge computing technologies and programming in Python--one of the world's most popular and fastest-growing languages. Please read the Table of Contents diagram inside the front cover and the Preface for more details. In the context of 500+, real-world examples ranging from individual snippets to 40 large scripts and full implementation case studies, you'll use the interactive IPython interpreter with code in Jupyter Notebooks to quickly master the latest Python coding idioms. After covering Python Chapters 1-5 and a few key parts of Chapters 6-7, you'll be able to handle significant portions of the hands-on introductory AI case studies in Chapters 11-16, which are loaded with cool, powerful, contemporary examples. These include natural language processing, data mining Twitter® for sentiment analysis, cognitive computing with IBM® WatsonTM, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop®, SparkTM and NoSQL databases, the Internet of Things and more. You'll also work directly or indirectly with cloud-based services, including Twitter, Google TranslateTM, IBM Watson, Microsoft® Azure®, OpenMapQuest, PubNub and more. Features 500+ hands-on, real-world, live-code examples from snippets to case studiesIPython + code in Jupyter® NotebooksLibrary-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal codeRich Python coverage: Control statements, functions, strings, files, JSON serialization, CSV, exceptionsProcedural, functional-style and object-oriented programmingCollections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series and DataFramesStatic, dynamic and interactive visualizationsData experiences with real-world datasets and data sourcesIntro to Data Science sections: AI, basic stats, simulation, animation, random variables, data wrangling, regressionAI, big data and cloud data science case studies: NLP, data mining Twitter®, IBM® WatsonTM, machine learning, deep learning, computer vision, Hadoop®, SparkTM, NoSQL, IoTOpen-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn®, Keras and more Register your product to gain access to updated chapters and material, as well as downloads, future updates, and/or corrections as they become available. See inside book for more information. …

Paperback. Condizione: new. Paperback. Written for programmers with a background in another high-level language, Python for Programmers uses hands-on instruction to teach todays most compelling, leading-edge computing technologies and programming in Pythonone of the worlds most popular and fastest-growing languages. In the context of 500+, real-world examples ranging from individual snippets to 40 large scripts and full implementation case studies, youll use the interactive IPython interpreter with code in Jupyter Notebooks to quickly master the latest Python coding idioms. After covering Python Chapters 1-5 and a few key parts of Chapters 6-7, youll be able to handle significant portions of the hands-on introductory AI case studies in Chapters 11-16, which are loaded with cool, powerful, contemporary examples. These include natural language processing, data mining Twitter for sentiment analysis, cognitive computing with IBM Watson, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop, Spark and NoSQL databases, the Internet of Things and more. Youll also work directly or indirectly with cloud-based services, including Twitter, Google Translate, IBM Watson, Microsoft Azure, OpenMapQuest, PubNub and more. 500+ hands-on, real-world, live-code examples from snippets to case studies IPython + code in Jupyter Notebooks Library-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal code Rich Python coverage: Control statements, functions, strings, files, JSON serialisation, CSV, exceptions Procedural, functional-style and object-oriented programming Collections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series & DataFrames Static, dynamic and interactive visualisations Data experiences with real-world datasets and data sources Intro to Data Science sections: AI, basic stats, simulation, animation, random variables, data wrangling, regression AI, big data and cloud data science case studies: NLP, data mining Twitter, IBM Watson, machine learning, deep learning, computer vision, Hadoop, Spark, NoSQL, IoT Open-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn, Keras and more Please note - this is the professional version of the title. For classroom use we recommend the academic version of the title, which is ISBN 9780135404676. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Paperback. Condizione: New. The professional programmer's Deitel® guide to Python® with introductory artificial intelligence case studies Written for programmers with a background in another high-level language, Python for Programmers uses hands-on instruction to teach today's most compelling, leading-edge computing technologies and programming in Python--one of the world's most popular and fastest-growing languages. Please read the Table of Contents diagram inside the front cover and the Preface for more details. In the context of 500+, real-world examples ranging from individual snippets to 40 large scripts and full implementation case studies, you'll use the interactive IPython interpreter with code in Jupyter Notebooks to quickly master the latest Python coding idioms. After covering Python Chapters 1-5 and a few key parts of Chapters 6-7, you'll be able to handle significant portions of the hands-on introductory AI case studies in Chapters 11-16, which are loaded with cool, powerful, contemporary examples. These include natural language processing, data mining Twitter® for sentiment analysis, cognitive computing with IBM® WatsonTM, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop®, SparkTM and NoSQL databases, the Internet of Things and more. You'll also work directly or indirectly with cloud-based services, including Twitter, Google TranslateTM, IBM Watson, Microsoft® Azure®, OpenMapQuest, PubNub and more. Features 500+ hands-on, real-world, live-code examples from snippets to case studiesIPython + code in Jupyter® NotebooksLibrary-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal codeRich Python coverage: Control statements, functions, strings, files, JSON serialization, CSV, exceptionsProcedural, functional-style and object-oriented programmingCollections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series and DataFramesStatic, dynamic and interactive visualizationsData experiences with real-world datasets and data sourcesIntro to Data Science sections: AI, basic stats, simulation, animation, random variables, data wrangling, regressionAI, big data and cloud data science case studies: NLP, data mining Twitter®, IBM® WatsonTM, machine learning, deep learning, computer vision, Hadoop®, SparkTM, NoSQL, IoTOpen-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn®, Keras and more Register your product to gain access to updated chapters and material, as well as downloads, future updates, and/or corrections as they become available. See inside book for more information. …

Paperback. Condizione: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

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Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

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Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

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