dataprep.eda: a newcomer in data analysis
In this article I show you how to use the new arrival of data analysis with Python: datapre.eda
All to understand and practice A.I. in a simple way
In this section of my blog you’ll be able to find some informations and usage around data preparation. I will also try some data preparation tools.
In this article I show you how to use the new arrival of data analysis with Python: datapre.eda
Discover in this article how to use the Open Source DataExplore tool to visualize and even manipulate your data.
Analyze your data effortlessly with the pandas_profiling Python library.
Find out in this article how to use distance algorithms and the Fuzzywuzzy library to compare strings.
preparing the datasets in a Machine Learning project is a very important step that should not be neglected, otherwise you risk over evaluating your model (over-fitting) or quite simply the opposite (under fitting). In this article we will go through the essential steps for this delicate operation.
This article shows you how to detect links between observation variables.
To follow up on my article on the management of character strings, here is a first part which will allow us to have a progressive approach to the processing of this type of data. Far from any semantic approach (which will be the subject of a later post) we will discuss here the technique of bags of words