Category Archives: Data Science

How to split your dataset to train and test datasets using SciKit Learn

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 from the training set you used earlier. Read more...

Handle missing data in your training dataset with SciKit Imputer

 

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 the dataset. But that’ll not be the case always. Read more...

Label Encoder vs. One Hot Encoder in Machine Learning

MachineLearning

If you’re new to Machine Learning, you might get confused between these two – Label Encoder and One Hot Encoder. These two encoders are parts of the SciKit Learn library in Python, and they are used to convert categorical data, or text data, into numbers, which our predictive models can better understand.  Read more...