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 word...
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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 kn...
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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....
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Not a lot of us have heard of Affective Computing. Most people I have spoken to about this didn't know anything about Affective Computing. So I thought, I'll just write an intro, explaining what I ha...
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More in The fastText Series. In our previous post, we saw what n-grams are and how they are useful. Before that post, we built a simple text classifier using Facebook’s fastText library. In this p...
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More in The fastText Series. N-gram is probably the easiest concept to understand in the whole machine learning space, I guess. An N-gram means a sequence of N words. So for example, “Medium blog”...
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More in The fastText Series. Text classification is a pretty common application of machine learning. In such an application, machine learning is used to categorise a piece of text into two or more...
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It’s very common these days to come across these terms - data science, artificial intelligence, machine learning, deep learning, neural networks, and much more. But what do these buzzwords actually m...
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Everybody wants to do machine learning these days. Machine learning, data science, artificial intelligence, deep learning, neural network — these have become some of the most used phrases in the tech...
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