Search Results for "data capture framework"

The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking.

Synth is an open-source data-as-code tool that provides a simple CLI workflow for generating consistent data in a scalable way. Use Synth to generate correct, anonymized data that looks and quacks like production. Generate test data fixtures for your development, testing, and continuous integration. Generate data that tells the story you want to tell. Specify constraints, relations, and all your semantics. Seed development and environments and CI. Anonymize sensitive production data. Create...

On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms,...

benerator is a framework for creating realistic and valid high-volume test data, used for load and performance testing and showcase setup. Data is generated from an easily configurable metadata model and exported to databases, XML, CSV or flat files.

DATA Gen™ Test Data Generator offers facilities to automate the task of creating test data for new or existing data bases. It helps lower the programming effort required, while reducing manual test data generation errors and the ripple effect that they cause on production systems, users and maintenance.

JRandO is a test data generator or better test object generator framework. It can be used in JUnit tests or in performance test (for e.g. using JMeter). It may also be useful in anonymization of data or in a simulation environment.