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portada The Future of Data Science and Parallel Computing: A Road to Technological Singularity (en Inglés)
Formato
Libro Físico
Idioma
Inglés
N° páginas
52
Encuadernación
Tapa Blanda
Dimensiones
27.9 x 21.6 x 0.3 cm
Peso
0.15 kg.
ISBN13
9781721132911

The Future of Data Science and Parallel Computing: A Road to Technological Singularity (en Inglés)

Ganapathi Pulipaka (Autor) · Createspace Independent Publishing Platform · Tapa Blanda

The Future of Data Science and Parallel Computing: A Road to Technological Singularity (en Inglés) - Pulipaka, Ganapathi

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Reseña del libro "The Future of Data Science and Parallel Computing: A Road to Technological Singularity (en Inglés)"

Amazon's #1 Bestseller Dr. Ganapathi Pulipaka is a Chief Data Scientist and SAP Technical Lead for one of the largest firms in the world. He is also a PostDoc Research Scholar in Computer Science Engineering in Big Data Analytics, Machine Learning, Robotics, IoT, Artificial Intelligence as part of Doctor of Computer Science program from Colorado Technical University, CO with another PhD in Data Analytics, Information Systems, and Enterprise Resource Management, California University, Irvine. A technology leader in artificial intelligence, SAP development, and solution architecture. A project/program manager for application development of SAP systems, machine learning, deep learning systems, application development management, basis, infrastructure, and consulting delivery services offering expertise in delivery execution and executive interaction. Experienced implementing ASAP, Agile, Agile ASAP 8, HANA ASAP 8, Activate, Prince2, SCRUM, and Waterfall SDLC project methodologies. Implemented multiple SAP programs/projects managing a team size of 60+ members, managing budget more than $5M to $10M with SAP backend databases of Oracle, IBM DB2, Sybase, Informix, MS SQL server on Mac OS and Linux environments. His background is in Computer Science with a professional skillset and two decades of management and hands-on development experience in Machine Learning in TensorFlow, Python, and R, Deep Learning in TensorFlow, Python, and R, SAP ABAP S/4 HANA 1609, SAP S/4 H HANA 1710, SAP IBP on SAP Cloud Platform, Big Data, IaaS, IoT, Data Science, Apache Hadoop, Apache Kafka, Apache Spark, Apache Storm, Apache Flink, SQL, NoSQL, Tableau, PowerBI, Mathematics, Data Mining, Statistical Framework, SIEM, SAP, SAP ERP/ECC 6.0 NetWeaver Portals, SAP PLM, cProjects, R/3, BW, SRM 5.0, CRM 7.4, 7.3, 7.2, 7.1, 7.0, Java, C, C++, VC++, SAP CRM-IPM, SAP CRM- Service management, SAP CRM-Banking, SAP PLM Web UI 7.47, xRPM, SCM 7.1 APO, DP, SNP, SNC, FSCM, FSCD, SCEM, EDI. CRM ABAP/OO, ABAP, CRM Web UI/BOL/GENIL/ABAP Objects, SAP Netweaver Gateway (OData), SAP Mobility, SAP Fiori, Information Security, CyberSecurity, Governance, Risk Controls, and Compliance, SAP Fiori HANA, ABAP Webdynpros, BSPs, EDI/ALE, CRM Middleware, CRM Workflow, JavaScript, SAP KW 7.3 SAP Content server, SAP TREX Server, SAP KPro, SAP PI (PO), SAP BPC, Script logics, Azure, SAP BPM, SAP UI5, SAP BRM, Unix, Linux, macOS, and always looking for patterns in data and performing extractions to provide new meanings and insights through algorithms and analytics.

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