Machine Learning

Summary: Notes on machine learning concepts, models, and applications. Last updated: 2026-08-20

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2026

• An Enhanced National-Scale Urban Tree Canopy Cover Dataset for the United States: Code for paper showing how to upscale Landsat data to predict high-resolution tree canopy cover. Related: Remote_Sensing, Data. Keywords: machine learning, Landsat, tree canopy, USGS, land cover

2024

• Groundnut Yield Modeling - Crop Yield Python: Colab notebook for groundnut crop yield prediction using machine learning in Python. Related: Agriculture, Python. Keywords: machine learning, crop yield, agriculture, Python, Colab

• What's wrong with R-squared: Explanation of R2 limitations in regression evaluation and recommended alternatives. Related: Deep_Learning, Data. Keywords: machine learning, regression, R-squared, model evaluation, statistics

Earlier

• Pearson and Spearman Correlation Twitter Thread: Twitter thread explaining the differences between Pearson and Spearman correlation coefficients. Related: Data. Keywords: machine learning, statistics, correlation, Pearson, Spearman

• Visualization of ML Algorithms: Visual demonstrations and implementations of common machine learning algorithms. Related: Python. Keywords: machine learning, visualization, algorithms, Python, education

• Why Data Scientists Should Decluster Geospatial Datasets: Article explaining declustering techniques for handling spatially biased geospatial training data. Related: Data. Keywords: machine learning, geospatial, declustering, spatial bias, data science

• Model Evaluation Course Material: Sebastian Raschka's course material on model evaluation, comparison, and selection in machine learning. Related: Data, Python. Keywords: machine learning, model evaluation, cross-validation, statistics, Python

• PCA Visualisation: Interactive visual explanation of Principal Component Analysis. Related: Data. Keywords: machine learning, PCA, dimensionality reduction, visualization

• NASA Machine Learning Model for Global Landslide Nowcasts: NASA ML model that doubles accuracy for global landslide nowcasting. Related: Remote_Sensing. Keywords: machine learning, landslide, NASA, nowcasting, geospatial

• PyCaret: Low-code, end-to-end machine learning Python library for rapid ML model development. Related: Python. Keywords: machine learning, Python, PyCaret, low-code, AutoML

• Raster Vision Library: Azavea's deep learning framework for satellite and aerial imagery classification, detection, and segmentation. Related: Deep_Learning, Remote_Sensing, Python. Keywords: machine learning, deep learning, satellite imagery, Raster Vision, Python

• RF vs GTB Variable Importance: Comparison of variable importance between Random Forest and Gradient Tree Boosting models. Related: Data. Keywords: machine learning, Random Forest, Gradient Boosting, feature importance

• Farm Boundary Detection - Approaches: Review of crop field boundary detection approaches and main challenges in satellite imagery. Related: Deep_Learning, Remote_Sensing. Keywords: machine learning, deep learning, farm boundary, field detection, satellite

• Sampling Equal Area Grid Projection for Land Cover: Paper on equal-area grid projection sampling strategies for land cover classification. Related: Remote_Sensing. Keywords: machine learning, sampling, land cover, equal area, projection

• Parametric vs Non-Parametric Time Series Forecasting - Review: Comprehensive review comparing parametric and non-parametric time series forecasting methods. Related: XArray, Climate. Keywords: time series, forecasting, parametric, non-parametric, machine learning

• Time Series Analysis Slides: Course slides on time series analysis theory for climate and environmental data. Related: XArray, Climate, Data. Keywords: time series, analysis, climate, education, statistics

• EPA Guide for River Trend Analysis: EPA technical notes on trend analysis methods for river flow and water quality data. Related: XArray, Water_Resources, Data. Keywords: time series, trend analysis, rivers, water, EPA, statistics

• TerrSet - Time Series Prediction Software: Clark Labs TerrSet software for geospatial time-series analysis, prediction, and change detection. Related: XArray, Remote_Sensing. Keywords: time series, TerrSet, geospatial, prediction, change detection, software