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What is NLP?
While maintaining its simplicity and generalizing ability, the automatic summary extraction algorithm is able to work in difficult situations. For example, many implementations fail on texts with foreign languages or unique dictionary associations that are not contained in standard text arrays.
2021-10-01, by Frank Flegg, Director at BNI East Midlands
#NLP || #Tech || #Algorithms ||
Table of contents:
- Introduction to NLP with Sentiment Analysis in Text Data
- What is Natural Language Processing (NLP)?
- Data Cleaning
Introduction to NLP with Sentiment Analysis in Text Data
People communicate using some form of language and use either text or speech. Now for computers to interact with people, computers need to understand the natural language that people speak. Natural language processing is about teaching computers to understand, process, and use natural languages.
In this article, we will look at some of the common techniques used in NLP problems. And let's create a simple sentiment analysis model using movie reviews to predict positive or negative ratings.
What is Natural Language Processing (NLP)?
NLP is one of the branches of artificial intelligence that works with the analysis, understanding and generation of living languages in order to interact with computers both orally and in writing, using natural languages instead of computer ones.
Data Cleaning
During Data Cleaning, we remove special characters, symbols, punctuation, html tags, etc. from the original data, which do not contain any information useful for the model and only add noise to the data. Read more: doctranslator
What to remove from the source data and what not depends on the problem statement. For example, if you are working with text from the field of economics or business, signs such as $ or other currency symbols may contain hidden information that you do not want to lose. But in most cases, we delete them.
