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#Datascience
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Using Tableau to detect outliers and ruptures
To do that, we are going to get the outliers of a dataset, the change points and a piecewise approximation.
Applying a row-wise function to a Pandas dataframe
More than 3 years ago, we posted a comparative study about Looping over Pandas data using a CPU.
Python Spatial Join with GeoPandas (and GEOS)
The purpose of this post is to perform an "efficient" spatial join in Python. What is a spatial join?
Goldbach's Comet with Numba and Datashader
This Python notebook is about computing and plotting Goldbach function. It requires some basic mathematical knowledge, nothing fancy!
Quick data exploration with pandas, matplotlib and seaborn
In this JupyterLab Python notebook we are going to look at the rate of coronavirus [COVID-19] cases in french departments [administrative divisions of…
Optuna and XGBoost on a tabular dataset
The purpose of this Python notebook is to give a simple example of hyperparameter optimization [HPO] using Optuna and XGBoost.
Saving a tf.keras model with data normalization
Training a DL model might take some time, and make use of some special hardware.
Benford's law and the population of french cities
In this Python notebook, we are going to look at Benford's law, which predicts the leading digit distribution, when dealing with some real-world…
Logistic regression with JAX
JAX is a Python package for automatic differentiation from Google Research. It is a really powerful and efficient library.
