Sap Netweaver Portal Technology The Complete Reference

SAP NetWeaver Portal Technology

SAP® Project System Handbook

Centralize and Control Enterprise Project Management Plan, execute, and track projects across the entire lifecycle using SAP Project System (PS) and the in-depth information contained in this comprehensive volume. SAP Project System Handbook explains how to configure PS for optimal performance, design structures and networks, create project blueprints, generate cost estimates and materials demands, and use the latest SAP tools. You will find full details on scheduling work, automating and tracking billing and POs, triggering events, and integrating with most other SAP modules. An invaluable reference to PS transaction codes is also included. Configure and customize SAP Project System Build PS objects, networks, and Work Breakdown Structures Use customer and service projects to track sales and billing Understand Assembly Processing concepts Create integrated cost, settlement, and resource plans Develop financial, workforce, and materials management blueprints Perform resource-related billing using Dynamic Item Processor Profiles Simulate and automatically generate sales documents, POs, and quotations Manage corporate investments with IM structures and AUCs Construct timesaving Project, Network, and Milestone Templates Extend functionality with the Project Builder, Planning Board, and ProMan

Large Language Model-Based Solutions

Learn to build cost-effective apps using Large Language Models In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you'll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine tuning. The author sheds light on techniques for optimizing inference, like model quantization and pruning, as well as different and affordable architectures for typical generative AI (GenAI) applications, including search systems, agent assists, and autonomous agents. You'll also find: Effective strategies to address the challenge of the high computational cost associated with LLMs Assistance with the complexities of building and deploying affordable generative AI apps, including tuning and inference techniques Selection criteria for choosing a model, with particular consideration given to compact, nimble, and domain-specific models Perfect for developers and data scientists interested in deploying foundational models, or business leaders planning to scale out their use of GenAI, Large Language Model-Based Solutions will also benefit project leaders and managers, technical support staff, and administrators with an interest or stake in the subject.