All-in-one IoT Platform - Device management, data collection, processing and visualization.
- visualization
- iot
- iot-platform
- mqtt
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All-in-one IoT Platform - Device management, data collection, processing and visualization.
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.
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
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.
The Open Source Feature Store for AI/ML
Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark
Koalas: pandas API on Apache Spark
:truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
One advanced and mature open-source MPP (Massively Parallel Processing) database. Open source alternative to Greenplum Database.
GraphFrames is a package for Apache Spark which provides DataFrame-based Graphs
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
📈 Collect customer event data from your apps. (Note that this project only includes the API collector, not the visualization platform)
oneAPI Data Analytics Library (oneDAL)
Multi-Modal Database replacing MongoDB, Neo4J, and Elastic with 1 faster ACID solution, with NetworkX and Pandas interfaces, and bindings for C 99, C++ 17, Python 3, Java, GoLang 🗄️
High-performance, time-indexed object storage for robotics and industrial IoT
Tree diagrams with JavaScript :evergreen_tree: :chart_with_upwards_trend:
Read and write Neuroglancer datasets programmatically.
Data-mining and Visualization components for RAD Studio
Big Data essentials: Hadoop, MapReduce, Spark. Explore tutorials and demos in Jupyter notebooks—most are self-contained and live, ready to run with a click.
A curated list of awesome Qlik extensions and resources for Qlik Sense and QlikView
A general-purpose data analysis engine radically changing the way batch and stream data is processed
Estimating the number of clusters in a data set via the gap statistic. Implemented in H2O-3
Implementation of Partitioning Around Medoids (PAM) in H2O-3