The Pleasure of Finding Things Out: A blog by James Triveri

Introduction to Markov Chain Monte Carlo – The Metropolis-Hastings Algorithm

September 21, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

Markov Chain Monte Carlo (MCMC) is a class of algorithms used to sample from probability distributions when direct sampling is difficult or inefficient. It leverages Markov chains to explore the target distribution and Monte Carlo methods to per...

$f(x|\theta)$

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Introduction to Folium

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

Learning geospatial data science is crucial in today’s data-driven world for several reasons. Geospatial data science enables individuals to understand and analyze complex spatial phenomena, including natural disasters, urbanization, climate cha...

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Working with Geospatial Vector Data

August 17, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

Geospatial vector data is a way of representing geographic features in a digital format using points, lines, and polygons. Unlike raster data, which represents geographic data as a grid of cells or pixels, vector data represents features more pr...

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Working with Geospatial Vector Data

August 17, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

Geospatial vector data is a way of representing geographic features in a digital format using points, lines, and polygons. Unlike raster data, which represents geographic data as a grid of cells or pixels, vector data represents features more pr...

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Composite Estimators in scikit-learn

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

To build a composite estimator in scikit-learn, transformers are usually combined with other transformers and/or predictors (such as classifiers or regressors). The most common tool used for composing estimators is a Pipeline. The Pipeline is often used in combination with ColumnTransformer or FeatureUnion which concatenate the output of transformers ... [...Read more...]

Querying SQL Server from Pandas

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

If you research how to connect to a database from Python, many examples use the pyodbc library, which, aptly named, creates a connection to any ODBC-compatible database. However, connections with pyodbc itself are uni-directional: Data can be re... [...Read more...]

Querying SQL Server from Pandas

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

If you research how to connect to a database from Python, many examples use the pyodbc library, which, aptly named, creates a connection to any ODBC-compatible database. However, connections with pyodbc itself are uni-directional: Data can be re... [...Read more...]

Using the Singular Value Decomposition for Image Compression

April 28, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

The Singular Value Decomposition (SVD) is a mathematical technique used in linear algebra to decompose a matrix into three other matrices. Specifically, for any matrix , the SVD is a factorization of the form where: is . is (unitary with o...

$X$

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Hyperparameter Search and Classifier Threshold Selection

April 28, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

The following notebook demonstrates how to use GridSearchCV to identify optimal hyperparameters for a given model and metric, and alternatives for selecting a classifier threshold in scikit-learn. First we load the breast cancer dataset. We will...

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Using the Singular Value Decomposition for Image Compression

April 28, 2024 | The Pleasure of Finding Things Out: A blog by James Triveri

The Singular Value Decomposition (SVD) is a mathematical technique used in linear algebra to decompose a matrix into three other matrices. Specifically, for any matrix , the SVD is a factorization of the form where: is . is (unitary with or...

$X$

[...Read more...]

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Articles by The Pleasure of Finding Things Out: A blog by James Triveri

Introduction to Markov Chain Monte Carlo – The Metropolis-Hastings Algorithm

Introduction to Folium

Working with Geospatial Vector Data

Working with Geospatial Vector Data

Composite Estimators in scikit-learn

Querying SQL Server from Pandas

Querying SQL Server from Pandas

Using the Singular Value Decomposition for Image Compression

Hyperparameter Search and Classifier Threshold Selection

Using the Singular Value Decomposition for Image Compression