UiPath Certified Professional - General Track Certification UiPath-SAIv1 Exam Questions and Answers PDF

Deep learning is a subset of machine learning that uses multiple layers of artificial neural networks to learn from data and perform complex tasks. The term “deep” refers to the number of layers in the network, which can range from a few to hundreds or even thousands. Each layer consists of a set of nodes that perform mathematical operations on the input data and pass the output to the next layer. The network learns by adjusting the weights of the connections between the nodes based on the feedback from the desired output. Deep learning can handle various types of data, such as images, text, speech, or video, and can automatically extract features and patterns from them without human intervention. Deep learning is behind many applications of artificial intelligence, such as computer vision, natural language processing, speech recognition, and generative models123.

References: 1: What is Deep Learning? | IBM 2: What Is Deep Learning? Definition, Examples, and Careers | Coursera 3: Deep learning - Wikipedia

UiPath Communications Mining is a new capability to understand and automate business communications. It uses state-of-the-art AI models to turn business messages—from emails to tickets—into actionable data. It does this in real time and on all major business communications channels1. Natural Language Processing (NLP) is the branch of AI that deals with analyzing, understanding, and generating natural language. NLP enables UiPath Communications Mining to extract the most important data from any message, such as reasons for contact, data fields, and sentiment2. NLP also allows UiPath Communications Mining to deploy custom AI models in hours, not weeks, by using automatic labeling and annotation2.

References: 2 Communications Mining - Automate Business Communications | UiPath 1 Introducing UiPath Communications Mining | UiPath

 Entities are additional elements of structured data which can be extracted from within the verbatims. Entities include data such as monetary quantities, dates, currency codes, organisations, people, email addresses, URLs, as well as many other industry specific categories. Entities represent concepts, themes, and intents that are relevant to the business use case and can be used for filtering, searching, and analyzing the verbatims.

References:

Communications Mining - Entities

Communications Mining - Using Entities in your Application

Communications Mining - Configuring Entities