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NIRPY Research (@danielpelliccia@aus.social) @NirpyR

NirPy Research is an educational space for Python chemometrics. Learn Python and machine learning with examples using real data. Written by @DanielePellicc8

Joined May 2022
  • Tweets 179
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  • Followers 76
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#Python code to plot a correlation circle in PCA decomposition using @scikit_learn and @matplotlib
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I'll phasing out this account in the next few days. If you're on Mastodon, follow me at @danielpelliccia@aus.social, if you wish 😀
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📚 New post: The Kennard-Stone algorithm nirpyresearch.com/kennard-st…

The Kennard-Stone algorithm • NIRPY Research

The Kennard-Stone algorithm is a criterion to divide a dataset into a calibration and a validation subset. Here's an introduction to the method and a basic Python implementation.

nirpyresearch.com
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Big shout-out to our wonderful @Patreon supporters! Thanks folks for supporting us, so that we can keep the blog free for everyone. If you'd like to take a peek at the supporters perks, head here patreon.com/nirpyresearch
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PLS-Discriminant analysis on data with binary labels #Python #MachineLearning #chemometrics
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Style your spectral plots with @matplotlib styles 👌
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PLS Discriminant analysis is a variation of PLS for classification problems. Here's a tutorial on binary classification with PLS-DA in #Python with @scikit_learn and @matplotlib #chemometrics nirpyresearch.com/pls-discri…

PLS Discriminant Analysis for binary classification in Python • NIRPY Research

PLS Discriminant analysis is a variation of PLS able to deal with classification problems. Here's a tutorial on binary classification with PLS-DA in Python

nirpyresearch.com
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Strength of #coffee roast detected with #nearinfrared spectroscopy using PCA decomposition. 3D scatter plot of the first 3 principal components with @matplotlib in #Python
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Robust estimation of the covariance matrix and Mahalanobis distance for outliers detection in #Python. Scatter plot of the principal components color-coded according to the Mahalanobis distance with @matplotlib #MachineLearning
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PCA decomposition of #nearinfrared spectra of mixtures of milk and lactose-free milk in different proportions. 3D scatter plot of the first 3 principal components with @matplotlib in #Python
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A very gentle introduction to building fully-connected deep neural networks with @TensorFlow for regression analysis of spectral data. #nearinfrared #spectroscopy #chemometrics nirpyresearch.com/deep-neura…

Deep neural networks for spectral data regression with TensorFlow • NIRPY Research

This post introduces basic Python code to build fully-connected deep neural networks with TensorFlow for regression analysis of spectral data.

nirpyresearch.com
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📖 New application note: Detecting #lactose in lactose-free #milk with #nearinfrared spectroscopy #Python #chemometrics nirpyresearch.com/detecting-…

Detecting lactose in lactose-free milk with NIR spectroscopy • NIRPY Research

NIR spectroscopy can detect sources of allergens or intolerance in food. Here's an example of detecting lactose in lactose-free milk.

nirpyresearch.com
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Fourier filtering can be used to smooth #nearinfrared spectra. Here's an introduction to the theory and a #Python code implementation nirpyresearch.com/fourier-sp…

Fourier spectral smoothing method • NIRPY Research

Meet a fairly unknown member of the spectral smoothing family: the Fourier spectral smoothing method. Learn some theory and Python code implementation.

nirpyresearch.com
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Principal Component Regression  is linear regression done on Principal Components. Here's a tutorial on PCR for #nearinfrared spectroscopy using @scikit_learn and @matplotlib in #Python nirpyresearch.com/principal-…

Principal Component Regression in Python

An in-depth introduction to Principal Component Regression in Python using NIR data. PCR is the combination of PCA with linear regression. Check it out.

nirpyresearch.com
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📚Ridge #regression can be used as an alternative to PLS for variable selection in near-infrared #spectroscopy. Optimise the penalty term in ridge regression with GridSearchCV in @scikit_learn and #Python #MachineLearning #chemometrics
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Aquagrams chart the relative strength of the NIR absorbance of specific bands in water-based systems. Popular in aquaphotomics. Here's an example code using @matplotlib nirpyresearch.com/aquagrams-… #python #chemometrics #DataScience #Datavisualization #spectroscopy

Aquagrams with Python and Matplotlib • NIRPY Research

Aquagrams are diagrams charting the relative strength of the NIR reflectance or absorbance of specific bands in water-based systems. Here's an example code to plot an aquagram using Matplotlib.

nirpyresearch.com
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Bootstrap cross-validator consistent with other splitter classes in model_selection by @scikit_learn #Python #chemometrics #DataScience #MachineLearning for #spectroscopy
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Dimensionality reduction of your spectral data with the kernel trick. Kernel PCA with #Python @scikit_learn and @matplotlib See how it's done👇
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The code for dimensionality reduction with kernel PCA is here nirpyresearch.com/pca-kernel…

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Snippets and data from our blog github.com/nevernervous78/ni…

GitHub - nevernervous78/nirpyresearch: Snippets and data from the blog of Nirpy Research

Snippets and data from the blog of Nirpy Research. Contribute to nevernervous78/nirpyresearch development by creating an account on GitHub.

github.com
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Step-by-step PCA and kernel PCA on real #nearinfrared #spectroscopy data. nirpyresearch.com/pca-kernel… #Python #MachineLearning #chemometrics

PCA and kernel PCA explained • NIRPY Research

Gain a practical understanding of PCA and kernel PCA by learning to code the algorithms and test it on real spectroscopic data.

nirpyresearch.com
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