sktime
scientific-visualization-book
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| sktime | scientific-visualization-book | |
|---|---|---|
| 8 | 17 | |
| 7,404 | 10,057 | |
| 2.4% | - | |
| 9.8 | 3.6 | |
| 2 days ago | 3 months ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
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
scientific-visualization-book
- Scientific Visualization: Python and Matplotlib
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Which latest DS Skill you are working on currently?
knowing matplotlib really well gets really pro viz tbh, this https://github.com/rougier/scientific-visualization-book is the best resource for it imo. Its a bit more work but you can get really great results
- Book or web book recommendation request: a data visualization cookbook using Python for scientists.
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What's New in Matplotlib 3.6.0
I had the same problem until I found this tutorial:
https://github.com/rougier/matplotlib-tutorial
If you wan something deeper the same person has written a book:
https://github.com/rougier/scientific-visualization-book
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looking for scientific visualization book in julia
i saw this one : > https://github.com/rougier/scientific-visualization-book
- Scientific-Visualization-Book - None
- 📘 An open access book on scientific visualization using python and matplotlib, h/t @MikeTamir
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Dyson hatching (dungeon map)
I re-created the hatching using matplotlib as shown here.
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Dungeon map rendering using matplotlib
From the open access book "Scientific Visualization: Python + Matplotlib. Code: dungeon.py
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Ask HN: What is the best book on data visualization in 2021?
For python this open access book is excellent: https://github.com/rougier/scientific-visualization-book
What are some alternatives?
darts - A python library for user-friendly forecasting and anomaly detection on time series.
datatable - A Python package for manipulating 2-dimensional tabular data structures
tslearn - The machine learning toolkit for time series analysis in Python
db-benchmark - reproducible benchmark of database-like ops
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
DataFrame - C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and contiguous memory storage
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.
Altair - Declarative statistical visualization library for Python
scikit-hts - Hierarchical Time Series Forecasting with a familiar API
oz - Data visualizations in Clojure and ClojureScript using Vega and Vega-lite
scikit-learn - scikit-learn: machine learning in Python
mplcyberpunk - "Cyberpunk style" for matplotlib plots