Search Results for "data collection algorithm"

StreamAlert is a serverless, real-time data analysis framework that empowers you to ingest, analyze, and alert on data from any environment, using data sources and alerting logic you define. Computer security teams use StreamAlert to scan terabytes of log data every day for incident detection and response. Incoming log data will be classified and processed by the rules engine. Alerts are then sent to one or more outputs. Rules are written in Python; they can utilize any Python libraries or...

Soma - System Omnichannel Marketing Analysis is an open-source solution for simplifying the processes of analyzing and predicting consumer behavior. With Soma, you can combine data from multiple systems and channels in the profile joining process. Interactions and behaviors registered as a part of a unique user create and show what a Customer Journey looks like. The data is subjected to an analysis process which enables the examination of the significance of individual touchpoints for the...

Store collected information and data properly using D0rgnizer (The organizer). Create cases, folders, files, and insert images. Compare information between files, and export data to share with your team. Useful for data collection in investigations, ethical hacking, and more.

...It works well with the Zipline open source backtesting library. At the core of pyfolio is a so-called tear sheet that consists of various individual plots that provide a comprehensive image of the performance of a trading algorithm. Here's an example of a simple tear sheet analyzing a strategy. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more.

We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community,...

The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded.

A set of services to allow for polling remote sites for data, displaying it on the local machine requesting said data, and moving that data anywhere else it needs to go.

PyPotrace is a Python programming language binding for Peter Selinger's Potrace raster to vector conversion algorithm. No separate Potrace library or application required!

Benetech Human Rights Program Utility Library: Collection of utilities used by the Benetech Human Rights programming for processing human rights data in preparation for statistical analysis. Library handles DSV files, name canonicalization, binarray, et

VFML -- Very Fast Machine Learning toolkit. A collection of tools, learners, and APIs for working with high-speed data streams and very large data sets.

nBoost is a suite of boosting algorithms designed to solve binary classification problems on data that is not linearly separable by a convex combination of base hypotheses, i.e. noisy data. WARNING: Active development. Underlying algorithm is unstable.