9781484280041 - advanced data analytics using python: with architectural patterns, text and image classification, and optimization techniques di mukhopadhyay, sayan; samanta, pratip (24 risultati)
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Paperback or Softback. Condizione: New. Advanced Data Analytics Using Python: With Architectural Patterns, Text and Image Classification, and Optimization Techniques. Book.
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Paperback. Condizione: New. Second Edition. Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language…processing, and computer vision in the cloud environment.Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analyticswith reinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application. What You'll LearnBuild intelligent systems for enterpriseReview time series analysis, classifications, regression, and clusteringExplore supervised learning, unsupervised learning, reinforcement learning, and transfer learning Use cloud platforms like GCP and AWS in data analyticsUnderstand Covers design patterns in Python Who This Book Is ForData scientists and software developers interested in the field of data analytics.
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Paperback. Condizione: new. Paperback. Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language proce…ssing, and computer vision in the cloud environment.Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analyticswith reinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application. What You'll LearnBuild intelligent systems for enterpriseReview time series analysis, classifications, regression, and clusteringExplore supervised learning, unsupervised learning, reinforcement learning, and transfer learning Use cloud platforms like GCP and AWS in data analyticsUnderstand Covers design patterns in Python Who This Book Is ForData scientists and software developers interested in the field of data analytics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Paperback. Condizione: new. Paperback. Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language proce…ssing, and computer vision in the cloud environment.Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analyticswith reinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application. What You'll LearnBuild intelligent systems for enterpriseReview time series analysis, classifications, regression, and clusteringExplore supervised learning, unsupervised learning, reinforcement learning, and transfer learning Use cloud platforms like GCP and AWS in data analyticsUnderstand Covers design patterns in Python Who This Book Is ForData scientists and software developers interested in the field of data analytics. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Paperback. Condizione: New. Second Edition. Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language…processing, and computer vision in the cloud environment.Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analyticswith reinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application. What You'll LearnBuild intelligent systems for enterpriseReview time series analysis, classifications, regression, and clusteringExplore supervised learning, unsupervised learning, reinforcement learning, and transfer learning Use cloud platforms like GCP and AWS in data analyticsUnderstand Covers design patterns in Python Who This Book Is ForData scientists and software developers interested in the field of data analytics.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image cla…ssification, optimization techniques, natural language processing, and computer vision in the cloud environment. 268 pp. Englisch.
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Über den AutorrnrnSayan Mukhopadhyay is a data scientist with more than 13 years of experience. He has been associated with companies such as Credit-Suisse, PayPal, CA Technology, CSC, and Mphasis. He has a deep…understanding of data a.
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classif…ication, optimization techniques, natural language processing, and computer vision in the cloud environment.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 268 pp. Englisch.
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classifi…cation, optimization techniques, natural language processing, and computer vision in the cloud environment.Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analyticswith reinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application. What You'll LearnBuild intelligent systems for enterpriseReview time series analysis, classifications, regression, and clusteringExplore supervised learning, unsupervised learning, reinforcement learning, and transfer learning Use cloud platforms like GCP and AWS in data analyticsUnderstand Covers design patterns in Python Who This Book Is ForData scientists and software developers interested in the field of data analytics.
