MetricOpta can also be used as a tool for creating custom data-driven applications for data driven analytics.
MetreNet provides a toolkit to build a variety of metrics in the data driven computing space, including traffic, performance, and latency.
Metronix provides a platform for building machine learning algorithms.
Metrix gives developers tools to integrate data from a variety.
Metrisp and Metrispy can be integrated with existing analytics software to build real-time and predictive analytics solutions.
MetricsAnalyzer provides a set of tools to create a custom metrics framework, which can then be used in a variety other analytics software, including Google Analytics and Evernote.
And MetricsTools provides a collection of tools for building metrics based on a wide variety of data sources.
Metriometer is a platform that aims to provide developers with tools to combine data from various sources to create custom metrics.
Metrinometer is based on the core tools from Metric optima.
Metrium is a cloud-based analytics platform for analyzing large-scale data sets.
Metra uses metrics to provide real-world insights and analytics.
Ametrix provides tools for analysing data from large data sets in real-space.
AMetrix is a framework for building real-life analytics using metrics.
The toolkit includes a tool called TensorFlow, which is a dataflow-based framework that supports high-performance computing, deep learning, machine learning, and distributed systems.
There are also tools that help developers create and implement metrics and analytics tools, including a framework called the TensorNet Framework.
For developers, Metric and MetricsOpta provide a collection for building data driven applications.
For the average web user, it is possible to leverage the toolkit and use it to build tools to use to optimize web pages.