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Natural Language Generation

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What is Natural Language Generation? Natural language generation (NLG) is the use of artificial intelligence (AI) programming to produce written or spoken narratives from a data set. Natural language generation (NLG) is the use of artificial intelligence (AI) programming to produce written or spoken narratives from a data set. NLG is related to human-to-machine and machine-to-human interaction, including computational linguistics, natural language processing (NLP) and natural language understanding (NLU). Research about NLG often focuses on building computer programs that provide data points with context. Sophisticated NLG software can mine large quantities of numerical data, identify patterns and share that information in a way that is easy for humans to understand. The speed of NLG software is especially useful for producing news and other time- sensitive stories on the internet. At its best, NLG output can be published verbatim as web content. How NLG works? NLG is a multi-stage pro
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Text Analytics

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What is Text Analytics? Text analytics  combines a set of  machine learning , statistical and linguistic techniques to process large volumes of unstructured text or text that does not have a predefined format, to derive insights and patterns. It enables businesses, governments, researchers, and media to exploit the enormous content at their disposal for making crucial decisions. Text analytics uses a variety of techniques – sentiment analysis, topic modelling, named entity recognition, term frequency, and event extraction. What’s the Difference Between Text Mining and Text Analytics? Text mining and text analytics are often used interchangeably. The term text mining is generally used to derive qualitative insights from unstructured text, while text analytics provides quantitative results. For example, text mining can be used to identify if customers are satisfied with a product by analyzing their reviews and surveys. Text analytics is used for deeper insights, like identifying a patter
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Robotic Process Automation

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Robotic Process Automation Robotic process automation (RPA) is a software technology that makes it easy to build, deploy, and manage software robots that emulate humans actions interacting with digital systems and software. Just like people, software robots can do things like understand what’s on a screen, complete the right keystrokes, navigate systems, identify and extract data, and perform a wide range of defined actions. But software robots can do it faster and more consistently than people, without the need to get up and stretch or take a coffee  Robotic process automation streamlines workflows, which makes organizations more profitable, flexible, and responsive. It also increases employee satisfaction, engagement, and productivity by removing mundane tasks from their workdays.                            Types of RPA There are 3 major types of robotic process automation: attended automation, unattended automation, and hybrid RPA. 1. Attended Automation This type of bot resides on
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Deep Learning

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  Deep Learning in AI Deep learning is based on the branch of machine learning, which is a subset of artificial intelligence. Since neural networks imitate the human brain and so deep learning will do. In deep learning, nothing is programmed explicitly. Basically, it is a machine learning class that makes use of numerous nonlinear processing units so as to perform feature extraction as well as transformation. The output from each preceding layer is taken as input by each one of the successive layers. Deep learning models are capable enough to focus on the accurate features themselves by requiring a little guidance from the programmer and are very helpful in solving out the problem of dimensionality. Deep learning algorithms a re used, especially when we have a huge no of inputs and in the deep learning has been evolved by the machine learning  which itself is a subset of artificial intelligence and as the idea behind the  artificial intelligence  is to mimic the human behavior, so same
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Decision Management in AI

What is AI decision making? AI and decision management systems can help companies in making valid decisions by providing up-to-date and relevant information and performing analytic functions. Companies base their decisions on data available from management information systems as they reflect information that comes from the operations of their company. Combining AI and decision management systems can take decision-making to different levels. AI’s capabilities help these decision management systems in translating customer data into predictive models of key trends. This has helped marketing and consumer departments in customizing their efforts according to key demographics. AI AND DECISION MANAGEMENT: BENEFITS  Since its beginning, AI has played a revolutionary role in automating both knowledge based and non-knowledge based activities. Today, a huge amount of data is used for generating various models on a weekly basis or even on a daily basis, that help an organization in making decision
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Expert Systems in AI

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  What is an Expert System? An expert system is a computer program that is designed to solve complex problems and to provide decision-making ability like a human expert. It performs this by extracting knowledge from its knowledge base using the reasoning and inference rules according to the user queries. The expert system is a part of AI, and the first ES was developed in the year 1970, which was the first successful approach of artificial intelligence. It solves the most complex issue as an expert by extracting the knowledge stored in its knowledge base. The system helps in decision making for complex problems using  both facts and heuristics like a human expert . It is called so because it contains the expert knowledge of a specific domain and can solve any complex problem of that particular domain. These systems are designed for a specific domain, such as  medicine, science,  etc. The performance of an expert system is based on the expert's knowledge stored in its knowledge base
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Virtual Agents

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  WHAT IS A VIRTUAL AGENT? A virtual agent is, as described by Chatbots.org , "... a computer generated, animated, artificial intelligence virtual character that serves as an online customer service representative. It leads an intelligent conversation with users, responds to their  questions and performs adequate non-verbal behavior." In other words, if you have ever used online customer support to resolve an issue with your phone bill or chatted with a service desk agent at your job to reset a password, then you most likely interacted with a virtual agent. A shorter definition by  Tech Target  explains that "a virtual agent is a program based in artificial intelligence (AI) that provides automated customer service.” This concept, however, should not be confused with call center agents that work remotely, who can also be called “virtual agents”. Essentially, this technology can provide basic information to customers or employees, help guide the users through questions, a
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