ML | Treating Missing Values - Implementation in Python
source link: https://www.geeksforgeeks.org/videos/ml-treating-missing-values-implementation-in-python/
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- 05/04/2022
Python is a great Language to implement Machine learning. In working with ML models, some libraries play a very vital role in Python like NumPy, Pandas, scikit-learn. NumPy (Numerical Python) : It is one of the greatest Scientific and Mathematical computing library for Python. Platforms like Keras, Tensorflow have embedded Numpy operations on Tensors. The feature we are concerned with its power and easy to handle and perform an operation on Array. Pandas: This package is very useful when it comes to handling data. This makes it very easier to manipulate, aggregate and visualize data. MatplotLib: This library facilitates the task of powerful and very simple visualizations.In this video, we are going to see how to handle missing data in machine learning using Python implementation. We will cover some approaches are Drop columns, Drop rows, using fillna() methods and imputer.
Related article: https://www.geeksforgeeks.org/ml-handling-missing-values/ https://www.geeksforgeeks.org/k-nearest-neighbors-with-python-ml/ https://www.geeksforgeeks.org/ml-handle-missing-data-with-simple-imputer/
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