In our previous post, we discussed what is feature selection and why we need feature selection. In this post, we're going to look at the different methods used in feature selection. There are three ...
Read MoreMonth: July 2018
If you've come across a dataset in your machine learning endeavors which has more than one feature, you'd have also heard of a concept called Feature Selection. Today, we're going to find out what it ...
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Today we'll be looking at a simple Linear Regression example in Python, and as always, we'll be using the SciKit Learn library. If you haven't yet looked into my posts about data pre-processing, which...
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When you're working with a learning model, it is important to scale the features to a range which is centered around zero. This is done so that the variance of the features are in the same range. If a...
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When you're working on a model and want to train it, you obviously have a dataset. But after training, we have to test the model on some test dataset. For this, you'll a dataset which is different fro...
Read More Most often than not, you'll encounter a dataset in your data science projects where you'll have missing data in at least one column. In some cases, you can just ignore that row by taking it out of th...
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Update: SciKit has a new library called the ColumnTransformer which has replaced LabelEncoding. You can check out this updated post about ColumnTransformer to know more. If you're new to Machine L...
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