PyForecastTools
Forecast Verification/Validation Tools in Python (by drsteve)
awesome-experimental-standards-deep-learning
Repository collecting resources and best practices to improve experimental rigour in deep learning research. (by Kaleidophon)
PyForecastTools | awesome-experimental-standards-deep-learning | |
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1 | 1 | |
30 | 25 | |
- | - | |
3.7 | 2.0 | |
12 months ago | about 1 year ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 only |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
PyForecastTools
Posts with mentions or reviews of PyForecastTools.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-11.
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[P] Introducing confidenceinterval, the long missing python library for computing confidence intervals
Nice to see a python implementation of deLong's method - I've had to use pROC (in R) for that in the past. For binary event analysis (among other things) there's also https://github.com/drsteve/PyForecastTools, which also has bootstrapped confidence intervals, or analytic CI using Wald or Agresti-Coull. The terminology is from weather literature, but it covers a lot of the same ground.
awesome-experimental-standards-deep-learning
Posts with mentions or reviews of awesome-experimental-standards-deep-learning.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-11.
-
[P] Introducing confidenceinterval, the long missing python library for computing confidence intervals
Very neat! I will add this to https://github.com/Kaleidophon/experimental-standards-deep-learning-research :-)
What are some alternatives?
When comparing PyForecastTools and awesome-experimental-standards-deep-learning you can also consider the following projects:
pillow - Python Imaging Library (Fork)
yacs - YACS -- Yet Another Configuration System
awesome-deep-learning-music - List of articles related to deep learning applied to music
awesome-recruitment - List of my favourite recruitment things 💫
LiDAR-Guide - LiDAR Guide
orion - Asynchronous Distributed Hyperparameter Optimization.
software-papers - 📚 A curated list of papers for Software Engineers
baybe - Bayesian Optimization and Design of Experiments
PyForecastTools vs pillow
awesome-experimental-standards-deep-learning vs yacs
awesome-experimental-standards-deep-learning vs awesome-deep-learning-music
awesome-experimental-standards-deep-learning vs awesome-recruitment
awesome-experimental-standards-deep-learning vs LiDAR-Guide
awesome-experimental-standards-deep-learning vs orion
awesome-experimental-standards-deep-learning vs software-papers
awesome-experimental-standards-deep-learning vs baybe