Julio Cárdenas-Rodríguez

Apr 22

Push the limits of explainability — an ultimate guide to SHAP library

456

Ula La Paris

This is the best medium article on ML that I have ever read.

This is the best medium article on ML that I have ever read. Thank you !!

1 min read

This is the best medium article on ML that I have ever read.

Thank you !!

Apr 15

([a, b]))
return numerator / denominato…""
numerator = wasserstein_distance(a, b)
denominator = np.std(np.concatenate([a, b]))
return numerator / denominator if denominator != .0 else .0

Statistical Tests Won’t Help You to Compare Distributions

302

Samuele Mazzanti

very cool notation for an if statement ; I did not know you could do this. Thank you

1 min read

very cool notation for an if statement ; I did not know you could do this. Thank you

Apr 5

A First Look at Sklearn’s HistGradientBoostingClassifier

Martinson Ofori

Martin,

Martin, Using one-hot encoding might reduce the performance of this method. Also, you can handle categorical data directly:

1 min read

Martin,

Using one-hot encoding might reduce the performance of this method.

Also, you can handle categorical data directly:

Oct 17, 2021

Data Science with the Penguins Data Set: Bayesian Networks

Basics and benefits — This blog is part of my series on doing / learning data science using the penguins data set. In an previous post I described how to estimate conditional probabilities and conditional expectations. The example I showed included only two variables with only three levels each, leading to one 3X3 table…

Python

3 min read

Data Science with the Penguins Data Set: Bayesian Networks

Oct 17, 2021

Data Science with the Penguins Data Set: Conditional Probability in Python

How to compute probabilities and expectation values using pandas and numpy — This blog is part of my series on doing / learning data science using the penguins data set. Goal Over the years, I have encountered manuscripts, documentation, and blogs which mention that something is calculated, but it is not clear how it is calculated. …

Python

4 min read

Data Science with the Penguins data set: Conditional Probability

Oct 17, 2021

Data Science with the Penguins Data Set: Table of Contents

.I have decided to use the same data set for all my future blog posts about data science. These data were collected from 2007–2009 by Dr. …

Data Science

2 min read

Mar 15, 2021

A GLRM model generates the X and Y matrixes. X matrix has been obtained by calling: X.m = as.data.table(h2o.getFrame(m_glrm@model$representation_name))

How to cluster dataset with high dimensionality and mixed datatypes

Ellen Deng

Do you know how to do in python ?.

Do you know how to do in python ?. I am having a very hard time getting X. I can do it in Julia and R; The Python API for H2o runs, but I can't find X

1 min read

Do you know how to do in python ?. I am having a very hard time getting X. I can do it in Julia and R;

The Python API for H2o runs, but I can't find X

Aug 7, 2018

How to include data cleaning decisions in the tuning of machine learning hyperparameters in Python

The problem Data science practitioners must make decisions regarding the cleaning of data that are usually arbitrary, and that might affect the performance of the models we are trying to create. Some of these decisions are related to challenges such as: The number of levels needed for a given predictor…

Machine Learning

2 min read

Nov 9, 2017

Tuning scikit-learn parameters using optimization: Work smart not hard

The problem On previous posts I described how to perform non-linear curve fitting in Ptyhon and Julia. At their core non-linear and linear curve fitting (or regression) are optimization problems in which we find the parameters that minimize an objective function. The entire field of mathematical optimization is concerned with…

Python

2 min read

Tuning scikit-learn parameters using optimization: Work smart not hard

Nov 6, 2017

How to create an alias in Windows Powershell to launch Jupyter and Python

Python

1 min read