ABOUT THIS EPISODE
STUMPY is a powerful and scalable library that efficiently computes something called the matrix profile, which can be used for a variety of time series data mining tasks such as: pattern/motif (approximately repeated subsequences within a longer time series) discovery, anomaly/novelty (discord) discovery, shapelet discovery, semantic segmentation, density estimation, time series chains (temporally ordered set of subsequence patterns), and more!
Listen to the Episode!
English
United States
TRANSCRIPT 🔗
Are you the producer of this podcast?
Add a podcast transcript
Need Audio-to-Text?
Transcribe with Listen411 in Just 60 Seconds
SEARCH PAST EPISODES
Search past episodes of Open Source Directions hosted by OpenTeams.
OTHER EPISODES IN THIS PODCAST
Lale is a Python library for semi-automated data science. Lale makes it easy to
automatically select algorithms and tune hyperparameters of pipelines that are
compatible with scikit-learn, in a type-safe fashion. If you are a data scientist
who wants to experiment with automated machine learning, t…
Originally a port of the R package, pyjanitor has evolved from a set of convenient data cleaning
routines into an experiment with the method chaining paradigm. Data preprocessing usually consists
of a series of steps that involve transforming raw data into an understandable/usable format.
…
Jupyter Book lets you build an online book using a collection of
Jupyter Notebooks and Markdown files. Its output is similar to the
excellent Bookdown tool, and adds extra functionality for people
running a Jupyter stack.
Listen to the Episode!
Download
Bokeh is an interactive visualization library for modern web browsers.
It provides elegant, concise construction of versatile graphics, and
affords high-performance interactivity over large or streaming datasets.
Bokeh can help anyone who would like to quickly and easily make interactive
plots, das…
Disclaimer: The podcast and artwork embedded on this page are from Quansight, LLC, which is the property of its owner and not affiliated with or endorsed by Listen Notes, Inc.
EDIT
Thank you for helping to keep the podcast database up to date.