The key learning topics of this webinar include: common scenarios where data science techniques are being used in trading situations, how lack of engineering rigor or audit controls may affect the results in these situations, and how the common data science notebook paradigm can be embedded in not just in your environment - but in your applications to apply that rigor.
Data science applications to trading systems
Risks commonly encountered in nascent applications
How notebooks can be embedded in existing applications
Trading or risk management, to control access, and report on results
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