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Machine Learning Terms every manager should know

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  Getting started with AI? Perhaps you’ve already got your feet wet in the world of Machine Learning, but still looking to expand your knowledge and cover the subjects you’ve heard of but didn’t quite have time to cover? Rashtech - Web Designing and App Development 1. NLP – Natural Language Processing Natural Language Processing (NLP) is a common notion for a variety of Machine Learning methods that make it possible for the computer to understand and perform operations using human (i.e. natural) language as it is spoken or written. The most important use cases of Natural Language Processing are: Document Summarization is a set of methods for creating short, meaningful descriptions of long texts (i.e. documents, research papers). 2. Reinforcement learning Reinforcement Learning differs in its approach from the approaches we’ve described earlier. In RL the algorithm plays a “game”, in which it aims to maximize the reward. The algorithm tries different approaches “moves” using trial-a...
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How companies are making money by recommend system

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  Simply put, a recommender system is an AI algorithm (usually Machine Learning) that utilizes Big Data to suggest additional products to consumers based on a variety of reasons. These recommendations can be based on items such as past purchases, demographic info, or their search history. Rashtech - Web Designing and App Development 1. There are many types of recommender systems available Choosing the right type of recommender system is as important as choosing to utilize one in the first place. Here is a quick overview of the options available to you. The most important use cases of Natural Language Processing are: Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. 2. Reinforcement learning Reinforcement Learning differs in its approach from the approaches we’ve described earlier. In RL the algorithm pl...
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Deep Learning Chatbot – analysis and implementation

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  If you have a business with a heavy customer service demand, and you want to make your process more efficient, it’s time to think about introducing chatbots. In this blog post, we’ll cover some standard methods for implementing chatbots that can be used by any B2C business. Rashtech - Web Designing and App Development 1. Chatbots Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusantium doloremque laudantium, totam rem aperiam, eaque ipsa quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt explicabo. Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut odit aut fugit, sed quia consequuntur magni dolores eos qui ratione voluptatem sequi nesciunt. The most important use cases of Natural Language Processing are: Document Summarization is a set of methods for creating short, meaningful descriptions of long texts (i.e. documents, research papers). 2. Deep learning At this point, your data is prepared and you have chosen the right kind o...
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AI simplified: What computers are good at

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  Getting started with AI? Perhaps you’ve already got your feet wet in the world of Machine Learning, but still looking to expand your knowledge and cover the subjects you’ve heard of but didn’t quite have time to cover? Rashtech - Web Designing and App Development 1. Investment banks can use AI in six critical ways Natural Language Processing (NLP) is a common notion for a variety of Machine Learning methods that make it possible for the computer to understand and perform operations using human (i.e. natural) language as it is spoken or written. The most important use cases of Natural Language Processing are: Sentiment analysis aims to determine the attitude or emotional reaction of a person with respect to some topic – e.g. positive or negative attitude, anger, sarcasm. It is broadly used in customer satisfaction studies (e.g. analyzing product reviews). 2. Reinforcement learning Reinforcement Learning differs in its approach from the approaches we’ve described earlier. In RL the...
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