customer-segmentation
sktime
| customer-segmentation | sktime | |
|---|---|---|
| 1 | 8 | |
| 2 | 7,454 | |
| - | 1.7% | |
| 10.0 | 9.8 | |
| 3 months ago | 6 days ago | |
| Python | 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.
customer-segmentation
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Using oneAPI AI Toolkits from Intel and Accenture Part 2
$ git clone https://github.com/oneapi-src/customer-segmentation
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?
ai-transcribe - AI Starter Kit for the implementation of an AI transcribe system using Intel® Extension for PyTorch*
darts - A python library for user-friendly forecasting and anomaly detection on time series.
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
tslearn - The machine learning toolkit for time series analysis in Python
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
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.
scikit-hts - Hierarchical Time Series Forecasting with a familiar API
scikit-learn - scikit-learn: machine learning in Python
sysidentpy - A Python Package For System Identification Using NARMAX Models
greykite - A flexible, intuitive and fast forecasting library
sktime-dl - DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow
InceptionTime - InceptionTime: Finding AlexNet for Time Series Classification