As the data generated from IoT devices, mobile devices, applications, etc. increases at an hourly rate, creating a data lake to store all that data is getting crucial for almost any application at sc...
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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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If you're new to the world of data science, you'll know that lack of knowledge in statistics could sometimes be very frustrating and hinder progress. It becomes very important to know at least the ba...
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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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