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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In our previous post, we saw how to perform Backward Elimination as a feature selection algorithm to weed out insignificant features from our dataset. In this post, we'll checkout the next method for...
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When we're building a machine learning model, it is very important that we select only those features or predictors which are necessary. Suppose we have 100 features or predictors in our dataset. Tha...
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When you're starting your machine learning journey, you'll come across null hypothesis and the p-value. At a certain point in your journey, it becomes quite important to know what these mean to make ...
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We have seen methods such as fit(), transform(), and fit_transform() in a lot of SciKit's libraries. And almost all tutorials, including the ones I've written, only tell you to just use one of these ...
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In a very old post - Label Encoder vs. One Hot Encoder in Machine Learning - I had demonstrated how to use label encoding and one hot encoding to separate out categorical text data into numbers and d...
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I recently discovered that you can't invoke more than one Lambda function in AWS for an S3 event, with the same prefix and suffix (or just with the same suffix, which was the issue in my case). So I ...
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In the previous post, we tried to understand the basics of Apache's Kafka Streams. In this post, we'll build on that knowledge and see how Kafka Streams can be used both as streams and tables. St...
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