Publications by T. Moudiki
AutoML in nnetsauce (randomized and quasi-randomized nnetworks)
Content: Installing nnetsauce for Python Classification RegressionDisclaimer: I have no affiliation with the lazypredict project.A few days ago, I stumbled accross a cool Python package called lazypredict. Pretty well-designed, working, and relying on scikit-learn’s design.With lazypredict, you can rapidly have an idea of which scikit-learn model...
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Version v0.14.0 of nnetsauce for R and Python
Version v0.14.0 of nnetsauce is now available for R (hopefully a rapid installation) and Python on GitHub, PyPI and conda. It’s been mainly tested on Linux and macOS. For Windows users, you can try to install of course, but if it doesn’t work, please use WSL2.NEWSupdate and align as much as possible with R version (new plotting function for mul...
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An infinity of time series forecasting models in nnetsauce (Part 2 with uncertainty quantification)
As I said a few years ago, this is a family of univariate/multivariate time series forecasting models that I was supposed to present at R/Finance 2020 (this post is 100% Python) in Chicago, IL. But the COVID-19 decided differently.The more I thought about it, namely nnetsauce.MTS (still doesn’t have a more glamorous name), the more I thought ‘I...
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(News from) forecasting in Python with ahead (progress bars and plots)
A new Python version of ahead, v0.9.0 is now available on GitHub and PyPI.ahead is a Python and R package for univariate and multivariate time series forecasting, with uncertainty quantification (in particular, simulation-based uncertainty quantification).Here are the new features in v0.9.0:progress bars for possibly long calculations: the bootstra...
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Forecasting in Python with ahead
A new Python version of ahead is now available on GitHub and PyPI. ahead is a package (Python and R) for univariate and multivariate time series forecasting, with uncertainty quantification (in particular, simulation-based).Here are the new features:Align with R version (see https://github.com/Techtonique/ahead/blob/main/NEWS.md#version-070 and htt...
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Risk-neutralize simulations
A risk-neutral probability (in Quantitative Finance) is a probability measure in which, on average, all the risky assets return the risk-free rate. Risk-neutral probabilities are widely used for the pricing of derivative products. There are other advanced mathematical definitions of a risk-neutral probability that won’t be discussed here. In R pa...
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Comparing cross-validation results using crossval_ml and boxplots
Table of contents 0 – Install packages + global parameters 1 – Regression example 2 – Classification example 0 – Install packages + global parameters Let’s start by installing the main package, crossvalidation (version 0.5.0): 1st method: from R-universe (where you can also package’s long-form descriptions a.k.a vignettes) In R cons...
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Did you ask ChatGPT about who you are?
It all started with a bug in Python package BCN (BCN, for Boosted Configuration neural Networks), that I tried to solve with the traditional (and still efficient) tools for the job: search engines querying and Stackoverflow. Interested in learning more about BCNs? You can read this post and this post. Python package BCN is currently built on top...
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A new version of nnetsauce (randomized and quasi-randomized ‘neural’ networks)
Content: nnetsauce’s new version Installing nnetsauce for Python About nnetsauce for R nnetsauce’s new version A new version of nnetsauce, v0.12.0, is available on PyPI and for conda. It’s been mostly tested on Linux and macOS platforms. For Windows users: you can use the Windows Subsystem for Linux in case it doesn’t work directly ...
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nnetsauce on Pypi
Machine Learning and Deep Learning package nnetsauce (introduced here ) is now available on Pypi – and I’m so proud of it ;). Which means, you can install it by using the command line:pip install nnetsauce For more examples of use of this package, you can consult this post, or the package’s Github repo README.Related To leave a comment for ...
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