DataFrame
sktime
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| DataFrame | sktime | |
|---|---|---|
| 109 | 8 | |
| 2,258 | 7,387 | |
| - | 2.1% | |
| 9.2 | 9.8 | |
| about 15 hours ago | 2 days ago | |
| C++ | Python | |
| BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
DataFrame
- New multithreaded version of C++ DataFrame was released
- DataFrame: NEW Data - star count:2013.0
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C++ DataFrame vs. Polars
For a while, I have been hearing that Polars is so frighteningly fast that you shouldn’t look directly at it with unprotected eyes. So, I finally found time to learn a bit about Polars and write a very simple test/comparison for C++ DataFrame vs. Polars.
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C++ Show and Tell - July 2023
I have worked on C++ DataFrame for the past 5+ years in my spare times. It is comparable to Pandas or R data.frame, although it includes a lot more functionality.
- Allocators; one of the ignored souls of STL
sktime
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Keras-tuner tuning hyperparam controlling feature size
I would recommend you to read the following paper: https://arxiv.org/abs/1909.04939 and their implementation: https://github.com/hfawaz/InceptionTime . Moreover, check out sktime: https://github.com/sktime/sktime
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Does anyone know a trusted Python package for applying Croston's Time series method?
I initially used the SkTime's Croston class SKTime Croston but when I try to get the fitted values using the steps in the discussion on github, the values are the same, a straight line throughout the in-sample to ou-of-sample predictions.
- Forecasting three months ahead.
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I Need Your Help: Convincing Reasons for Python over C# for ML Pipeline?
Time series -> https://github.com/alan-turing-institute/sktime have a look and have fun :)
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Good python time series libraries?
SKTime
- Scikit-Learn Version 1.0
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Sktime: Machine Learning for Time Series
https://github.com/alan-turing-institute/sktime
It provides specialized time series algorithms and scikit-learn compatible tools to build, tune and validate time series models for multiple learning problems.
sktime is built by an active open-source community, working together during regular meetings, workshops and sprints. For new contributors, we provide mentoring sessions and tutorials.
If you are interested in contributing or just a chat about the project, feel free to submit a PR or just reach out to us. We welcome all kinds of contributions: code, API design, testing, documentation, outreach, mentoring and more.
- Darts: Non-Facebook alternative for timeseries forecasting
What are some alternatives?
datatable - A Python package for manipulating 2-dimensional tabular data structures
darts - A python library for user-friendly forecasting and anomaly detection on time series.
db-benchmark - reproducible benchmark of database-like ops
tslearn - The machine learning toolkit for time series analysis in Python
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
zhetapi - A C++ ML and numerical analysis API, with an accompanying scripting language.
Kats - Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
faiss - A library for efficient similarity search and clustering of dense vectors.
scikit-hts - Hierarchical Time Series Forecasting with a familiar API
scientific-visualization-book - An open access book on scientific visualization using python and matplotlib
scikit-learn - scikit-learn: machine learning in Python