Natural Language Techniques for every Data Scientist to know - adiraislamriya00 - 08-30-2023
If you are preparing to work or already work in the field of Data Science , know that it has been growing a lot in the market, but a field that is still little talked about is Natural Language Processing , which is very important for these professionals. The so-called NLP – Natural Language Process – is still little debated in the context of Data Science, but we want to change that. Thinking about it, we prepared today's special article. Good reading! What is NLP? Natural Language Process (NLP) or Natural Language Processing (NLP) is a technique created from the articulation between Data Science, Artificial Intelligence and linguistics, with the objective of “translating” human language for data processing from the construction of text processing models. Have you noticed that most answering services we use today initially put us through an automated response system.
Sometimes we receive a convenient response to our contact, but on other occasions it is as if the machine does not understand what we are trying to express. This is where the studies developed at NLP come in to make this type of experience as USA Phone Number List as possible, raising the level of understanding between machines and human beings. It may seem like a science fiction film , but it is already a reality on the market! See how it all works below. NLP operation NLP works by using language techniques, removing anything that could harm the understanding of the message and focusing on what is essential for the person and is executable for the system. For example, in the WhatsApp service of a service company, we can imagine the following situation. When the customer gets in touch and sends a “Hello” in the message, he usually receives an automatic message back, thanking him for contacting him and giving basic information related to the services offered.
Usually, options are suggested with what is most wanted by customers in general. It could be location, opening hours and delivery time. If the customer replies “I would like information about the payment method”, the removal technique will be applied to clean the message and make it executable so that the system can respond to the customer's demand. In the aforementioned example, the system acts by eliminating what is not essential in the message (from/about/to…) and focusing on what is executable (inform payment method). All of this is done very quickly so that the customer receives something like: “Methods of payment: cash, debit and credit card, which can be paid in up to 3 installments.”. data science NLP Why so much interest in Natural Language? There is a worldwide movement to optimize the interaction between machines and humans prioritizing the consumer experience.
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