MAPIE
glasgow-litter
MAPIE | glasgow-litter | |
---|---|---|
1 | 2 | |
1,164 | 3 | |
2.7% | - | |
9.7 | 6.1 | |
5 days ago | 7 months ago | |
Jupyter Notebook | Jupyter Notebook | |
BSD 3-clause "New" or "Revised" License | MIT 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.
MAPIE
-
How to calculate confidence level of a regression model?
Did some research and apparently there are number of ways and regression seems to be quite hard and no straightforward answer. Came across MAPIE (https://github.com/scikit-learn-contrib/MAPIE) which predicts a upper and lower range of values.. how can I then calculate the confidence for a given prediction?
glasgow-litter
- Exploring the relationships between deprivation and litter on the streets of Glasgow
-
Is this realistic for a undergraduate senior project?
Seems like you should be able to do this considering this project has a great outline for you to follow on a similar project: https://github.com/Garee/glasgow-litter
What are some alternatives?
data-science-notes - Notes of IBM Data Science Professional Certificate Courses on Coursera
TrashMob - Source Code for TrashMob.eco
pycaret - An open-source, low-code machine learning library in Python
100DaysofMLCode - My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:
tsai - Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
PyABSA - Sentiment Analysis, Text Classification, Text Augmentation, Text Adversarial defense, etc.;
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
TACO - 🌮 Trash Annotations in Context Dataset Toolkit
60-Days-of-Data-Science-and-ML - 60 Days of Data Science and ML