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Introduction to Datafication - Goniwada, Shivakumar R.

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        Présentation Introduction To Datafication de Goniwada, Shivakumar R. Format Broché

         - Livre Informatique

        Livre Informatique - Goniwada, Shivakumar R. - 31/05/2023 - Broché - Langue : Anglais

        . .

      • Auteur(s) : Goniwada, Shivakumar R.
      • Editeur : Apress L.P.
      • Langue : Anglais
      • Parution : 31/05/2023
      • Format : Moyen, de 350g à 1kg
      • Nombre de pages : 296
      • Expédition : 452
      • Dimensions : 23.5 x 15.5 x 1.7
      • ISBN : 9781484294956



      • Résumé :

        This book presents the process and framework you need to transform aspects of our world into data that can be collected, analyzed, and used to make decisions. You will understand the technologies used to gather and process data from many sources, and you will learn how to analyze data with AI and ML models.
        Datafication is becoming increasingly prevalent in many areas of our lives, from business to education and healthcare. It has the potential to improve decision-making by providing insights into patterns, trends, and correlation between seemingly unconnected pieces of data. This book explains the evolution, principles, and patterns of datafication used in our day-to-day activities. It covers how to collect data from a variety of sources, using technologies such as edge, streaming techniques, REST, and frameworks, as well as data cleansing and data lineage. A data analysis framework is provided to guide you in designing and developing AI and ML projects, including the details of sentiment and behavioral analytics.
        Introduction to Datafication teaches you how to engineer AI and ML projects by using various methodologies, covers the security mechanisms to be applied for datafication, and shows you how to govern the datafication process with a well-defined governance framework.
        What You Will Learn
        Understand the principles and patterns to be adopted for datafication Gain techniques for sourcing and mining data, and for sharing data with a data pipeline Leverage the AI and ML algorithms most suitable for datafication Understand the data analysis framework used in every AI and ML project Master the details of sentiment and behavioral analytics through practical examples Utilize development methodologies for datafication engineering and the related security and governance framework
        Who This Book Is For
        Students, data scientists, data analysts, and AI and ML engineers

        Biographie:
        Shivakumar R Goniwada is a renowned author, inventor, and technology leader with more than 23 years of experience in architecting cutting-edge cloud-native, data analytics, and event-driven systems. He currently holds a position as Chief Enterprise Architect at Accenture, where he leads a team of highly skilled technology enterprise and cloud architects. Throughout his career, Shivakumar has successfully led numerous complex projects across various industries and geographical locations. His expertise has earned him ten software patents in areas such as cloud computing, polyglot architecture, software engineering, and IoT. He is a sought-after speaker at global conferences and has made significant contributions to the field through his publications. Shivakumar R Goniwada holds a Master's degree in Technology Architecture and certifications in Google Professional, AWS, and data science. He also completed an Executive MBA at the prestigious MIT Sloan School of Management. His notable books include Cloud-Native Architecture and Design and Introduction to Datafication, both published by Apress....

        Sommaire:

        Chapter 1: Introduction to Datafication.- Chapter 2: Datafication Principles, Patterns, and Methodologies.- Chapter 3: Datafication Analytics.- Chapter 4: Datafication Pipeline.- Chapter 5: Data Analysis.- Chapter 6: Sentiment Analysis.- Chapter 7: Behavioral Analysis.- Chapter 8: Datafication Engineering.- Chapter 9: Datafication Governance.- Chapter 10: Datafication Security.

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