DearPy3D
evidently
| DearPy3D | evidently | |
|---|---|---|
| 4 | 13 | |
| 82 | 5,196 | |
| - | 2.1% | |
| 6.7 | 9.7 | |
| over 2 years ago | about 13 hours ago | |
| C++ | 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.
DearPy3D
-
How does one make their own GUI from scratch? (no GUI libraries)
Dear PyGui is awesome and supports creating node editors. 3D is not really supported yet (although matrix functions are), but future versions will support 3D. The core developers are very much interested in 3D rendering. As a little test, Hoffstadt created DearPy3D. He is currently working on Pilotlight, which is still early stages and eventually will be the core of Dear PyGui version 3.
-
The hand-picked selection of the best Python libraries released in 2021
Just a quick update since then is that Dear PyGui has reached version 1.0 and the API is now stable with a proper deprecation policy. Additional features include support for extremely dynamic tables, became faster still, introduction of the first steps into 3D and drawing transformations, support for multiple fonts, node editor and many small improvements and bug fixes. There are still many ideas for future development, including more 3D.
-
Best gui framework for fast 2d operations and 3d render?
With regard to 3D, are you aware of DearPy3D by the same developers (still under development, also available under the MIT license)?
-
Dear PyGui 3D Engine (Marvel)
hoffstadt/Marvel: Dear PyGui 3D Engine (early development) (github.com)
evidently
- Evidently: An open-source ML and LLM observability framework
-
10 Open Source MLOps Projects You Didn’t Know About
Evidently Evidently is an open source monitoring tool built by Evidently AI to help data scientists identify drifts in data, label, model performance changes, and run custom tests. Evidently works with tabular and textual data, including embeddings. In short, it is a tool to evaluate, test, and monitor machine learning models in production.
-
20 examples of LLM-powered applications in the real world
The database is maintained by the team behind Evidently, an open-source tool for LLM and ML evaluation and observability. Give us a star on GitHub to support the project!
-
[P] Free open-source ML observability course: starts October 16 🚀
Hi everyone, I’m one of the creators of Evidently, an open-source (Apache 2.0) tool for production ML monitoring. We’ve just launched a free open course on ML observability that I wanted to share with the community.
-
Free Open-source ML observability course
Evidently itself is an open-source ML monitoring tool with 3m+ downloads so it's fairly popular https://github.com/evidentlyai/evidently. The course will show it but also other OSS tools like Mlflow and Grafana.
Disclaimer: I am one of the people working on Evidently.
-
Batch ML deployment and monitoring blueprint using open-source
Repo:https://github.com/evidentlyai/evidently/tree/main/examples/integrations/postgres_grafana_batch_monitoring
- Looking for recommendations to monitor / detect data drifts over time
- evidently: Evaluate and monitor ML models from validation to production
-
State of the Art data drift libraries on Python?
Thank you for your answer. I'm trying it today and the the other libraries mentioned + https://github.com/evidentlyai/evidently
-
Package for drift detection
evidently: https://github.com/evidentlyai/evidently
What are some alternatives?
skweak - skweak: A software toolkit for weak supervision applied to NLP tasks
great_expectations - Always know what to expect from your data.
DearPyGui - Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
magnum - Lightweight and modular C++11 graphics middleware for games and data visualization
whylogs - An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
finetuner - :dart: Task-oriented embedding tuning for BERT, CLIP, etc.
MLflow - Open source platform for the machine learning lifecycle
processing - Source code for the Processing Core and Development Environment (PDE)
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
AugLy - A data augmentations library for audio, image, text, and video.
dvc - 🦉 ML Experiments and Data Management with Git