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Technology and Solutions

Extracting meaningful insights and discovering underlying mechanisms from unstructured data is, at its core, a creative process.  Without fundamental tools and techniques, the process is clumsy and inefficient, perhaps impossible. 

Research libraries

Data management, cleaning, and analysis

The internet is full of data science and statistical learning libraries, most of them open source and well documented: it's possible to quickly find a library that implements some specific operation quickly and (most likely) correctly.  Along with these benefits, there are also drawbacks:  

  • The user needs to know exactly which technique/tool to use and which implementation of it is appropriate and cobble together different tools from different sources

  • In a production environment, managing many open-source libraries is risky and challenging

  • APIs and functionality change from time to time, potentially (silently) breaking dependent code

  • Regularly reviewing and conforming to each library's license terms adds compliance burden. 

tpalib is solves a number of these problems by providing

  • a single license

  • a curated set of tools for predictive modelling problems that work together

  • managed updates and API consistency

  • responsive support

Custom Tools

Model and data visualization

An amazing model is useless if there's no way to use it and a perfect forecast is worthless if the decision makers can't see and understand the results.  We believe that as much time should be spend understanding a model and its results as researching and developing it in the first place.

To help with all phases of a data/predictive modelling project, we can create:

  • Dashboards: Visualize data and results historically and as they evolve in the future

  • Simulators: Understand model output, run what-if scenarios

  • Data collection tool: gather data from users, websites, documents in a structured and easy to use way

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