Solving Nonobvious Problems
Sean Law, a principal data scientist at Charles Schwab, discusses his role in solving nonobvious problems using data science and R&D. He highlights the importance of leveraging modern technologies and tools in the PY data stack for rapid prototyping and proof of concepts. Sean also introduces Stumpy, a Python package based on matrix profiles, which helps find nearest neighbors in time series analysis.In this clip
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Data Skeptic
Matrix Profiles in Stumpy
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