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Top 11 Jupyter Notebook Clustering Projects
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InfluxDB
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WallStreetBets_BigDataAnalysis
Research project aimed to classify the best stock research posts from r/WallStreetBets for you. 😏
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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radius-constrained-kmeans
Codes for "No More Than 6FT Apart: Robust K-Means via Radius Upper Bounds", ICASSP 2022
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CSGO-Pro-Gear-Performance-and-EDA
Modeling Professional (CS:GO) Gamer's Accuracy Performance Based on Gear and Settings, and Exploratory Data Analysis.
Project mention: [P] I created a parallelized implementation of Agglomerative clustering that's many times faster than existing implementations and has a better runtime | /r/datascience | 2023-07-24Here is the code: https://github.com/porterehunley/RACplusplus. It would be great to have some people try it out (and find the bugs)!
Project mention: We're building PyPOTS: a Python toolbox for data mining on Partially-Observed Time Series | /r/learnprogramming | 2023-06-19Due to all kinds of reasons like failures of collection sensors, communication errors, and unexpected malfunctions, missing values are common to see in time series from the real-world environment. No matter whether we like them or not, missing data makes partially-observed time series (POTS) a pervasive problem in open-world modeling and prevents advanced data analysis. Although this problem is important, the area of data mining on POTS still lacks a dedicated toolkit. PyPOTS is created to fill in this gap. PyPOTS (pronounced "Pie Pots") is the first (and so far the only) Python toolbox/library specifically designed for data mining and machine learning on partially-observed time series (POTS), namely, incomplete time series with missing values, A.K.A. irregularly-sampled time series, supporting tasks of imputation, classification, clustering, and forecasting on POTS datasets. It is born to become a handy toolbox that is going to make data mining on POTS easy rather than tedious, to help engineers and researchers focus more on the core problems in their hands rather than on how to deal with the missing parts in their data. PyPOTS will keep integrating classical and the latest state-of-the-art data mining algorithms for partially-observed multivariate time series. For sure, besides various algorithms, PyPOTS has unified APIs together with detailed documentation and interactive examples across algorithms as tutorials. Feedback, questions, and contributions are all very welcome! Website: https://pypots.com Paper link: https://arxiv.org/abs/2305.18811 GitHub repo: https://github.com/WenjieDu/PyPOTS Tutorials: https://github.com/WenjieDu/BrewPOTS Docs: https://docs.pypots.com
Jupyter Notebook Clustering related posts
- We're building PyPOTS: a Python toolbox for data mining on Partially-Observed Time Series
- [R][P] A Python package for unsupervised mix data types clustering
- Hierarchical clustering algorithm
- New clustering algorithms like DBSCAN and OPTICS?
- DBSCAN ALternatives?
- Show HN: DenseClus, clustering for categorical and numeric data
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A note from our sponsor - InfluxDB
www.influxdata.com | 24 Apr 2024
Index
What are some of the best open-source Clustering projects in Jupyter Notebook? This list will help you:
Project | Stars | |
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1 | pycaret | 8,385 |
2 | hdbscan | 2,671 |
3 | WallStreetBets_BigDataAnalysis | 165 |
4 | amazon-denseclus | 90 |
5 | RACplusplus | 43 |
6 | BrewPOTS | 39 |
7 | Machine-Learning-Algorithms | 25 |
8 | wahlomat_analysis | 10 |
9 | Mixclu | 9 |
10 | radius-constrained-kmeans | 2 |
11 | CSGO-Pro-Gear-Performance-and-EDA | 1 |
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