covid19-severity-prediction
lockdowndates
| covid19-severity-prediction | lockdowndates | |
|---|---|---|
| 1 | 3 | |
| 227 | 6 | |
| 0.4% | - | |
| 0.0 | 0.0 | |
| 6 months ago | over 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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.
covid19-severity-prediction
lockdowndates
- Python package to help with feature engineering in machine learning for data during the covid-19 pandemic!
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Python package to aid with feature engineering data during the covid-19 pandemic!
u/ColdPorridge hey there - if you download lockdowndates version 0.0.4 from pypi or Conda you can now get access to the masks restrictions data! Check it out and let me know what ya think :) https://github.com/seanyboi/lockdowndates
What are some alternatives?
california-coronavirus-scrapers - The open-source web scrapers that feed the Los Angeles Times California coronavirus tracker.
Data-science - Collection of useful data science topics along with articles, videos, and code
Open-Risk-Manual-PdfBooks - Collection of PdfBooks extracted from the Open Risk Manual
DataDrivenDynSyst - Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
covid19za - Coronavirus COVID-19 (2019-nCoV) Data Repository and Dashboard for South Africa
Deep_XF - Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.
finite-element-networks - Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks" at ICLR 2022
StravaKudos - :running: :dart: Predicting Strava Kudos on my own activities using the given activity's attributes.
hyperlearn - 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
Digital-Learning-During-COVID19-EDA - In this project, we will be using data analysis tools to figure out trends in digital learning and how it is effective towards improvised communities. We will be comparing districts and states on factors like demography, internet access, learning product access, and finance.