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Machine Learning

2024

  • Groundnut Yield Modeling - Crop Yield Python: Colab notebook for groundnut crop yield prediction using machine learning in 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. [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. [Keywords: machine learning statistics correlation Pearson Spearman]

  • Visualization of ML Algorithms: Visual demonstrations and implementations of common machine learning algorithms. [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. [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. [Keywords: machine learning model evaluation cross-validation statistics Python]

  • PCA Visualisation: Interactive visual explanation of Principal Component Analysis. [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. [Keywords: machine learning landslide NASA nowcasting geospatial]

  • PyCaret: Low-code, end-to-end machine learning Python library for rapid ML model development. [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. [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. [Keywords: machine learning Random Forest Gradient Boosting feature importance]

  • Vector Geo Embedding Similarity Search: Tools for geospatial vector embedding similarity search using ML approaches. [Keywords: machine learning embeddings geospatial similarity search]

  • Farm Boundary Detection - Approaches: Review of crop field boundary detection approaches and main challenges in satellite imagery. [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. [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. [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. [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. [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. [Keywords: time series TerrSet geospatial prediction change detection software]