coiled-resources
stumpy
coiled-resources | stumpy | |
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2 | 6 | |
41 | 3,023 | |
- | 2.0% | |
4.0 | 7.9 | |
4 months ago | 7 days ago | |
Jupyter Notebook | Python | |
- | GNU General Public License v3.0 or later |
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coiled-resources
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Dask vs PySpark – Performance and Other Thoughts.
Here's an example notebook that shows computations on a 662 million row dataset.
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Dask vs PySpark - Performance and Other Thoughts.
I reran these computations on a 3 node Dask cluster (with Coiled platform) and the computations only took 2 minutes, see this notebook. Disclaimer: I work for Coiled.
stumpy
- Stumpy: Matrix profile time series analysis
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Time Series Analysis for air pollution data not aligned [R] [P]
Have you tried using STUMPY (https://github.com/TDAmeritrade/stumpy)?
- [D] STUMPY v1.11.0 Released for Modern Time Series Analysis
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[D][R] Clustering techniques for time series - MSc thesis
Haven't used it before, but I've seen a few powerpoints on https://github.com/TDAmeritrade/stumpy.
- Looking for a simple Time Series model for predicting stock prices
What are some alternatives?
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
pycrown - PyCrown - Fast raster-based individual tree segmentation for LiDAR data
awesome-time-series - Resources for working with time series and sequence data
kafkaml-anomaly-detection - Project for real-time anomaly detection using Kafka and python
dotmotif - A performant, powerful query framework to search for network motifs
luminol - Anomaly Detection and Correlation library
pyvtreat - vtreat is a data frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. Distributed under a BSD-3-Clause license.
dask-awkward - Native Dask collection for awkward arrays, and the library to use it.
numba-dpex - Data Parallel Extension for Numba
jertl - A minimum viable Python package for processing structured data
anomstack - Anomstack - Painless open source anomaly detection for your metrics 📈📉🚀
distributed-compute-on-aws-with-cross-regional-dask - Perform I/O intensive workloads on high-volume data sparsely located across multiple AWS regions through the use of Dask.