How to Develop Mission Critical Applications with PyIMSL and ActivePython
Recorded Wednesday, February 9, 2011
Join Rogue Wave’s Steve Lang and ActiveState’s Diane Mueller as they explore the benefits of using PyIMSL and ActivePython for developing your financial and scientific mission critical applications.
Rogue Wave’s IMSL Numerical Libraries are a comprehensive set of mathematical and statistical functions that you can embed into software applications. These libraries save you time with pre-written mathematical and statistical algorithms that you can embed into your Python applications in financial, science, technical, and business environments. Access to the libraries is now available through PyIMSL wrappers in ActivePython, the commercial Python distribution pre-compiled with popular Python packages.
This session will show you how to ensure that your mission critical application will move faster from prototype to production with less complexity, cost and risk. We will demonstrate the power of the combination of the ActivePython & Rogue Wave’s PyIMSL with a demonstration of an AutoRegressive Integrated Moving Average (ARIMA) time series model commonly used for understanding and forecasting future values of non-stationary time series.
By attending this webinar you will learn:
- how to access the PyIMSL Libraries with ActivePython,
- the breadth and depth of the analytic capabilities of PyIMSL and ActivePython, including a demo on time series forecasting
- example of charting using the matplotlib module
- the benefits of using commercial algorithms in your development process
- about additional feature that set PyIMSL’s AutoARIMA apart from other simple implementations