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Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)
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
An open-source, low-code machine learning library in Python
Build, Manage and Deploy AI/ML Systems
Anomaly detection related books, papers, videos, and toolboxes
A python library for user-friendly forecasting and anomaly detection on time series.
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.
A curated list of awesome R packages, frameworks and software.