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

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...

[...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...]

Demonstration of Principal Component Analysis

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

Principal Component Analysis (PCA) is a statistical technique used in the field of data analysis and machine learning for dimensionality reduction while preserving as much of the data’s variation as possible. It’s particularly useful when dealing...

$A = U \Sigma V^{T}$

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The Elbow Method for Determining the Number of Clusters in K-Means

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

The elbow method is a heuristic used in determining the optimal number of clusters in a k-means clustering algorithm. It is called the elbow method because it involves plotting the explained variation as a function of the number of clusters, and ...

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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...

$X$

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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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The Elbow Method for Determining the Number of Clusters in K-Means

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

The elbow method is a heuristic used in determining the optimal number of clusters in a k-means clustering algorithm. It is called the elbow method because it involves plotting the explained variation as a function of the number of clusters, and...

[...Read more...]

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

Introduction to Folium

Working with Geospatial Vector Data

Working with Geospatial Vector Data

Querying SQL Server from Pandas

Querying SQL Server from Pandas

Demonstration of Principal Component Analysis

The Elbow Method for Determining the Number of Clusters in K-Means

Using the Singular Value Decomposition for Image Compression

Hyperparameter Search and Classifier Threshold Selection

The Elbow Method for Determining the Number of Clusters in K-Means