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12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Apache Spark - A unified analytics engine for large-scale data processing

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

🛠 All-in-one web-based IDE specialized for machine learning and data science.

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

Simple Features for R

Google Earth Engine for R

Airborne LiDAR data manipulation and visualisation for forestry application

Spatiotemporal Arrays, Raster and Vector Data Cubes

R interface to Deck.gl and Mapbox

Interface to ChatGPT from R

An R package 📦 making it easy to query, preview, download and preprocess multiple kinds of spatial data 🛰 via R. All beta.

R package for fast and accurate raster zonal statistics

Landscape Metrics for Categorical Map Patterns 🗺️ in R

R Package for accessing and plotting Google Maps

WhiteboxTools R Frontend

Systematic conservation prioritization in R

Conversion between sf and geojson

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

bring sf to spark in production

An ecological niche model workflow based on dismo

UAV related Remote Sensing Toolbox

NetCDF-CF Geometry and Timeseries Tools for R: https://code.usgs.gov/water/ncdfgeom

Foreign Insight - WebApp providing insights about nationalities in Spain (Source: Instituto Nacional de Estadística)

An R Package to compile data sets of historic results from thoroughbred sales