Democratizing Artificial Intelligence with UiPath: Expand automation in your organization to achieve operational efficiency and high performance

· ·
· Packt Publishing Ltd
Libër elektronik
376
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Build an end-to-end business solution in the cognitive automation lifecycle and explore UiPath Document Understanding, UiPath AI Center, and DruidKey FeaturesExplore out-of-the-box (OOTB) AI Models in UiPathLearn how to deploy, manage, and continuously improve machine learning models using UiPath AI CenterDeploy UiPath-integrated chatbots and master UiPath Document UnderstandingBook Description

Artificial intelligence (AI) enables enterprises to optimize business processes that are probabilistic, highly variable, and require cognitive abilities with unstructured data. Many believe there is a steep learning curve with AI, however, the goal of our book is to lower the barrier to using AI. This practical guide to AI with UiPath will help RPA developers and tech-savvy business users learn how to incorporate cognitive abilities into business process optimization. With the hands-on approach of this book, you'll quickly be on your way to implementing cognitive automation to solve everyday business problems.

Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book will help you understand the power of AI and give you an overview of the relevant out-of-the-box models. You'll learn about cognitive AI in the context of RPA, the basics of machine learning, and how to apply cognitive automation within the development lifecycle. You'll then put your skills to test by building three use cases with UiPath Document Understanding, UiPath AI Center, and Druid.

By the end of this AI book, you'll be able to build UiPath automations with the cognitive capabilities of intelligent document processing, machine learning, and chatbots, while understanding the development lifecycle.

What you will learnDiscover how to bridge the gap between RPA and cognitive automationUnderstand how to configure, deploy, and maintain ML models in UiPathExplore OOTB models to manage documents, chats, emails, and morePrepare test data and test cases for user acceptance testing (UAT)Build a UiPath automation to act upon Druid responsesFind out how to connect custom models to RPAWho this book is for

AI Engineers and RPA developers who want to upskill and deploy out-of-the-box models using UiPath's AI capabilities will find this guide useful. A basic understanding of robotic process automation and machine learning will be beneficial but not mandatory to get started with this UiPath book.

Rreth autorit

Fanny Ip is a thought leader in Automation, Business Transformation, and Innovation. Currently, Fanny is the VP of the Automation Consulting Innovation Office at UiPath and leads a team of experienced management consultants to develop field-tested solutions for customers - from start-up, expand, to scale. Before joining UiPath, Fanny co-led McKinsey's Automation practice in North America and developed automation strategies for CxOs to deliver top-line revenue growth and achieve bottom-line impact. Before automation, Fanny has also led many business transformation projects at PwC Advisory and Deloitte Consulting. Fanny earned a BA in Economics from the University of Chicago and an MBA from the Anderson School of Management at UCLA. Originally from Hong Kong, Fanny resides in Los Angeles with her family.

Jeremiah is a multi-disciplined developer with a wide technical and operational lens. His initial passion for software development and implementation led him to automation and process efficiency. He enjoys working on and solving problems irrespective of size and technology. Jeremiah received his BA in Computer Science from New York University. His work history includes the likes of EY and McKinsey & Company, where he played roles within their Automation and Service Operations practices. He is currently a Director Manager within UiPath's Automation Consulting Innovation Office, assisting organizations drive adoption and scale of automation by managing digital transformation initiatives and developing hyper-automation frameworks and methodologies.

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