Lemmatization in Natural Language Processing (NLP) and Machine Learning Data Science by Sunny Srinidhi - February 26, 2020February 26, 20200 Lemmatization is one of the most common text pre-processing techniques used in Natural Language Processing (NLP) and machine learning in general. If you've already read my post about stemming of words in NLP, you'll already know that lemmatization is not that much different. Both in stemming and in lemmatization, we try to reduce a given word to its root word. The root word is called a stem in the stemming process, and it is called a lemma in the lemmatization process. But there are a few more differences to the two than that. Let's see what those are. How is Lemmatization different from Stemming In stemming, a part of the word is just chopped off at the tail end to arrive at
Stemming of words in Natural Language Processing, what is it? Data Science by Sunny Srinidhi - February 19, 20201 Stemming is one of the most common data pre-processing operations we do in almost all Natural Language Processing (NLP) projects. If you're new to this space, it is possible that you don't exactly know what this is even though you have come across this word. You might also be confused between stemming and lemmatization, which are two similar operations. In this post, we'll see what exactly is stemming, with a few examples here and there. I hope I'll be able to explain this process in simple words for you. Stemming To put simply, stemming is the process of removing a part of a word, or reducing a word to its stem or root. This might not necessarily mean we're reducing a word
Overriding Spring Boot properties in Amazon Lambda Tech by Sunny Srinidhi - February 11, 2020February 11, 20200 I want to start this post by bluntly saying that using a Spring Boot project as your Amazon Lambda function is a bad, bad idea, for so many reasons. I don’t want to get into that in this post. But sometimes, you can’t stop this from happening because you’re not calling the shots. Read more... “Overriding Spring Boot properties in Amazon Lambda”
Removing stop words in Java as part of data cleaning in Artificial Intelligence Data Science by Sunny Srinidhi - February 5, 2020February 5, 20200 More in The fastText Series. Working with text datasets is very common in data science problems. A good example of this is sentiment analysis, where you get social network posts as data sets. Based on the content of these posts, you need to estimate the sentiment around a topic of interest. When we're working with text as the data, there are a lot of words which we want to remove from the data to "clean" it, such as normalising, removing stop words, stemming, lemmatizing, etc. In this post, we'll see how we can remove stop words from our input text to clean our data so that our analysis is based only on the actual content of the data. But wait, what are stop