Nisheeth gupta (14 Ergebnisse)

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Taschenbuch. Zustand: Neu. Product Development Practices that Matter | Transform Market Opportunities and Technological Innovations into Successful Products | Nisheeth Gupta | Taschenbuch | 144 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844399813 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Product Development consists of activities totransform a market opportunity and technologicalinnovation into successful products. Several waves ofimprovements in technological innovation and prod¬uctdevelopment have already substantially enhancedcompanies¿ ability to deliver differentiated productsto markets faster, more efficiently, and with higherquality. However, the degree of success achieved hasvaried greatly between companies and even among unitswithin individual companies. Determining importantprocesses in the product development and theirrelationships with organizational and projectperformances are crucial to sustainable success inproduct development. Studying these relationshipswould give us insights into the product developmentdynamics. The objectives of this book are todetermine important product development processes andtheir relationship with each other and organizationalcapabilities.…

Zustand: New. pp. 350.

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Zustand: New. 2021. 1st Edition. Hardcover. . . . . .

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Gebunden. Zustand: New. Prateek Agrawal, PhD, completed his BTech in computer science engineering from Uttar Pradesh Technical University, Lucknow, India and MTech from ABV-IIITM, Gwalior, India. He also received his PhD from IKG-Punjab Technical University, Punjab, India. He has .

Hardcover. Zustand: Brand New. 350 pages. 0.39x0.39x0.39 inches. In Stock.

Zustand: New. 2021. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Neuware - MACHINE LEARNING AND DATA SCIENCEWritten and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia.Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms.These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.…