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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.

List of Data Science Cheatsheets to rule the world

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.

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

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/

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

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.

Various Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau

Simple Features for R

CoCalc: Collaborative Calculation in the Cloud

Easy access to official spatial data sets of Brazil in R and Python

Quantitative Financial Modelling Framework

Google Earth Engine for R

Airborne LiDAR data manipulation and visualisation for forestry application

R package for spatial data handling https://rspatial.github.io/terra/reference/terra-package.html

Spatiotemporal Arrays, Raster and Vector Data Cubes

A single-node analytical database engine with geospatial as a first-class citizen

Sustainable transport planning with R

R interface to Deck.gl and Mapbox

Technical analysis and other functions to construct technical trading rules with R

R package for downloading OpenStreetMap data

R interface to many NOAA data APIs

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