With the emergence of platforms that mainly rely on user-generated content, text data that contains valuable information about people's opinions and relationships became available to the public. Similarly, along with the digital revolution, surveys are now presented to a wider range of users, and taken in mobile devices. Our main medium for communication has become messaging applications or email. Medical records, research papers, newspaper articles are being created and stored in digital mediums.
All of these developments present businesses or individuals unique resources of information. Learning how to tap into these resources require a unique set of skills, and the methods used in this type of information-gathering is referred to as Text Analytics.
Businesses use this data to analyze customer and competitive data, pharmaceutical industry analyzes patents and research papers to increase the rate of new drug discovery, in academia, mining vast amounts of research papers increase the rate of knowledge gathering.
Text analytics is defined as the proces of extracting high quality information from text. Information is modeled and extracted using either linguistic, statistical, or machine learning techniques. The process consists of four main steps:
By taking Experfy's courses on Text Analytics and NLP, you will make sure that you're gaining a skill set that you can use to solve real-life, industry-specific problems. Whether it's analyzing open-ended survey responses, automatic processing of emails or messages, or investigating insurance claims, our courses will not only provide information about different methodologies, but they will also make sure that you understand how these methods are applied in real life.
According to Indeed, data scientists who possess NLP skills have an average annual salary of $138,000.
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Text classification: sentiment analysis and dialog act classification
Techniques for: Information Retrieval, Classification, Clustering & Recommenders
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