It is developed and licensed by MathWorks. It is a quick, stable and ensures solid algorithms for numerical computing language used entire academia and industry. Considered to be a well-suited language for mathematicians and scientists dealing with sophisticated mathematical needs such as Fourier transforms, signal processing, image processing, and matrix algebra.
MATLAB widely used in statistical analysis such as applications or day-to-day role requires intensive, advanced functionality in mathematical makes it a serious option for data science.
open source machine learning and artificial intelligence platform, https://www.h2o.ai
Driverless AI speeds up data science workflows by automating feature engineering, model tuning, ensembling and model deployment. More info https://www.h2o.ai/products/h2o-driverless-ai/
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.
Vadalog system, a Datalog-based system for performingcomplex logic reasoning tasks
SANSA is a big data processing engine for scalable processing of large-scale RDF data, please check SDA Web pages. SANSA uses Spark and Flink which offer fault-tolerant, highly available and scalable approaches to process massive sized datasets efficiently. SANSA provides the facilities for Semantic data representation, Querying, Inference, and Analytics.
SANSA-Stack’s core is a processing data flow engine that provides data distribution and fault tolerance for distributed computations over RDF large-scale datasets.