R is a free programming language and software environment for statistical computing and graphics.
There are 24,707 repositories under R topic.
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
mal - Make a Lisp
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.
🔥 Hugo website builder, Hugo themes & Hugo CMS. No code, build with widgets! 创建在线课程，学术简历或初创网站。
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.
An implementation of the Grammar of Graphics in R
A curated list of awesome R packages, frameworks and software.
Build and manage real-life data science projects with ease :rocket:
📚 Parameterize, execute, and analyze notebooks
Data Science at the Command Line
Realtime Web Apps and Dashboards for Python and R
A curated list of awesome machine learning interpretability resources.
🛠 All-in-one web-based IDE specialized for machine learning and data science.
A general-purpose tool for dynamic report generation in R
An interactive graphing library for R
Time Series Forecasting Best Practices & Examples
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components
Data Science Repo and blog for John Hopkins Coursera Courses. Please let me know if you have any questions.
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。
a curated list of R tutorials for Data Science, NLP and Machine Learning
lists of most popular repositories for most favoured programming languages (according to StackOverflow)
Open Data, more than 50 financial data. 提供超過 50 個金融資料(台股為主)，每天更新 https://finmind.github.io/