The authors of »Machine Learning with SAP«

Laboni Bhowmik

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Laboni Bhowmik is an SAP manufacturing consultant working at IBM since 2007. She has more than 15 years of experience with SAP solutions and technologies, including SAP Manufacturing Integration and Intelligence, SAP Manufacturing Execution, SAP Overall Equipment Effectiveness Management, SAPUI5, and SAP Cloud Platform. Laboni has led several large-scale SAP manufacturing implementation projects for multiple global clients. She is also extensively involved in progressing IBM’s SAP Digital Manufacturing and SAP Cloud Platform competency, including designing cutting-edge industry solutions, development, publications, and mentoring.
In this book, Laboni is the author of the chapters Machine Learning and Intelligent Enterprise, SAP Data Intelligence Machine Learning Business Services, Integrating Machine Learning with the Internet of Things and Blockchain, Industry Use Cases for Machine Learning Applications, and Conclusion and Roadmap.

Avijit Dhar

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Avijit Dhar is a senior consultant with IBM India. He has more than 15 years of experience in leading the design and implementation of multiple large-scale projects, particularly in the SAP manufacturing domain. He is also responsible for growing IBM’s SAP Internet of Things and machine learning practice. 
Avijit is a subject matter expert in user experience, Internet of Things, machine learning, and other emerging technologies, and is involved in designing numerous cutting-edge industry assets and solutions. Avijit is a coauthor of SAP Cloud Platform: Cloud-Native Development from SAP PRESS.

In this book, Avijit is the author of the chapters Machine Learning and Intelligent Enterprise, Machine Learning with SAP Data Intelligence, Building Scenarios Using Jupyter Notebook, Automated Machine Learning Data Science Automation, Conversational Artificial Intelligence, and Conclusion and Roadmap.

Ranajay Mukherjee

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Ranajay Mukherjee is a senior solution architect of SAP advanced analytics in IBM India. He has more than 21 years of experience in solutioning, leading, and delivering complex analytics projects across industries. Ranajay is a subject matter expert in data science, SAP HANA, SAP BW, and has extensively worked on the research, design, and development of machine learning and AI solutions using SAS, SPSS, R, and SAP HANA. He has held numerous leadership roles in IBM India, including SAP Enterprise HANA Practice Lead of IBM India and BW on HANA Conversion Factory Lead of IBM India. 
In 2019, Ranajay received the Outstanding Technical Achievement Award, recognizing his accomplishments within IBM's global business services, and has received the Eminence and Excellence Award from IBM India multiple times. Ranajay holds a Master of Statistics (MSTAT) and a Bachelor of Statistics (BSTAT) from Indian Statistical Institute, Kolkata. He is an Indian National Mathematics Olympiad awardee.

In this book, Ranajay is the author of the chapters Machine Learning Fundamentals, Implementation Lifecycle, Machine Learning on SAP HANA, SAP HANA Predictive Analysis Library and R Integration, Developing Applications with SAP HANA Predictive Analysis Library, and Conclusion and Roadmap.
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  • Cover of SAP Cloud Platform: Cloud-Native Development

    SAP Cloud Platform: Cloud-Native Development

    Gairik Acharya, Govind Bajaj, Avijit Dhar, Anup Ghosh, Asidhara Lahiri

    489 pages, hardcover

    Learn to build cloud applications from the ground up using SAP Cloud Platform. Explore the Neo and Cloud Foundry development environments; pick your backend language from a selection including Java, Node.js, and ABAP; and create a frontend with SAPUI5 and More about the book

    from $69.99

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    • Build and deploy applications on the Cloud Foundry and Neo environments
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  • Cover of Introducing Predictive Maintenance with SAP Predictive Asset Insights

    Introducing Predictive Maintenance with SAP Predictive Asset Insights

    Avijit Dhar

    65 pages

    How soon will your equipment need repairs? You'll learn how to use SAP Predictive Asset Insights to monitor the health of your equipment in real time and schedule maintenance when it is truly needed. Start by diving into key master More about the book

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    • Learn how machine learning facilitates predictive maintenance
    • Explore predictive models for distance, logistics regression, and more
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