Data science

Understanding the Graph Convolutional Network Propogation Model

February 5, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

Convolutional Neural networks (CNNs) have been found to be very effective at tasks such as facial recognition, video analysis, anomaly detections and semantic parsing. An image can be considered a graph with a very regular structure (i.e., pixel...

$H^{(l+1)} = \sigma(\tilde{D}^{-\frac{1}{2}} \tilde{A} \tilde{D}^{-\frac{1}{2}}H^{(l)}W^{(l)})$

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Using Dijkstra’s Algorithm to Find All Shortest Paths in a Graph

February 5, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

I always had trouble spelling Dijkstra correctly until someone pointed out “It’s just D, followed by i-j-k, then stra”. Once it was pointed out that i-j-k is represented sequentially in alphabetical order, spelling Dijkstra becomes trival - almo...

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Tuning Machine Learning models with GPopt’s new version Part 2

February 5, 2024 | T. Moudiki

Hyperparameter tuning with GPopt, based on Gaussian processes

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ML + XAI -> Strong GLM in Python

February 2, 2024 | Michael Mayer

In this post, we use Python to improve a simple GLM by insights from a boosted trees model.

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Generating Correlated Random Samples in Python

February 1, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

An analysis may require the ability to generate correlated random samples. For example, imagine we have monthly returns for three financial indicators over a 20 year period. We are interested in modeling these returns using parametric distributi...

$(0, \infty)$

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Bessel’s Correction

February 1, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

Bessel’s correction is the use of instead of in the sample variance formula where is the number of observations in a sample. This method corrects the bias in the estimation of the population variance. Recall that bias is defined as: where r...

$n$

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Denoising Signals using the FFT

February 1, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

The Discrete Fourier Transform (DFT) turns a data vector into a sum of sine/cosine components. The DFT is a Fourier series on data instead of analytic functions. Why do we perform the DFT? Because the features typically of interest aren’t always...

$\mathcal{O}(n \mathrm{log}(n))$

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GeoHashing from Scratch in Python

February 1, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

I recently became interested in GeoHashing, and wanted to develop an understanding of the algorithm with the goal of implementing it myself. I was surprised to find it to be quite simple and intuitive. In what follows, I’ll demonstrate how to ge...

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Gradient Descent for Logistic Regression

February 1, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

Within the GLM framework, model coefficients are estimated using iterative reweighted least squares (IRLS), sometimes referred to as Fisher Scoring. This works well, but becomes inefficient as the size of the dataset increases: IRLS relies on the...

$z = \boldsymbol{X} \boldsymbol{\theta}$

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Querying SQL Server with Pandas

February 1, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

Pandas is a powerful, flexible and easy to use open source data analysis and manipulation tool built on top of the Python programming language. It has become the data manipulation library of choice for Machine Learning and Data Science practition... [...Read more...]

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Python-bloggers

Data science news and tutorials - contributed by Python bloggers

Data science

Understanding the Graph Convolutional Network Propogation Model

Using Dijkstra’s Algorithm to Find All Shortest Paths in a Graph

Tuning Machine Learning models with GPopt’s new version Part 2

ML + XAI -> Strong GLM in Python

Generating Correlated Random Samples in Python

Bessel’s Correction

Denoising Signals using the FFT

GeoHashing from Scratch in Python

Gradient Descent for Logistic Regression

Querying SQL Server with Pandas