Register for this virtual workshop: Supercharging Python Performance

Join us and learn how to supercharge Python by using NumPy, SciPy, and pandas, all available through the Intel® oneAPI Analytics Toolkit (AI Kit). Performance increases up to 100 times (and more) can be achieved.

Using Intel® DevCloud as a platform, this workshop explores several NumPy aggregations, Universal Functions, Broadcasting, and other techniques.

The workshop delves into these topics:

NumPy constructs that perform the same tasks as common Python loops and list comprehensions applications.
NumPy Universal Function uses for fast and efficient time series labels.
Complicated logic conditions that slow down the pandas Apply function.

To create substantial performance gains, you can replace Python loop centric applications or list comprehension applications with smarter equivalents. In the process, your code will be more maintainable, more efficient, and much faster.

Tune in to the coding wisdom of the experts and launch swifter, more effective applications.

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Supercharging Python Performance

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Bob Chesebrough

Ben Odom