openvino_notebooks
Altair
| openvino_notebooks | Altair | |
|---|---|---|
| 80 | 43 | |
| 2,003 | 8,965 | |
| 5.7% | 1.3% | |
| 9.9 | 9.0 | |
| about 16 hours ago | 1 day ago | |
| Jupyter Notebook | Python | |
| Apache License 2.0 | 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.
openvino_notebooks
- FLaNK-AIM Weekly 06 May 2024
- FLaNK AI Weekly 18 March 2024
- FLaNK Stack Weekly 19 Feb 2024
- FLaNK Stack Weekly 12 February 2024
- FLaNK Stack 05 Feb 2024
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Optimum Intel OpenVino Performance
Also, credits for using zram in your VM setup; that's a smart hack for memory management. Have you tried tweaking other models like the ones in this OpenVINO notebook?
- FLaNK Stack Weekly 06 Nov 2023
- Trouvez-la plus vite
- Change your voice. FreeVC offers one-shot voice conversion, no text transcript required. Explore how OpenVINO powers AI solutions, see the code on GitHub.
- Vous aurez la banane
Altair
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Ask HN: What's the best charting library for customer-facing dashboards?
I like Vega-Lite: https://vega.github.io/vega-lite/
It’s built by folks from the same lab as D3, but designed as “a higher-level visual specification language on top of D3” [https://vega.github.io/vega/about/vega-and-d3/]
My favorite way to prototype a dashboard is to use Streamlit to lay things out and serve it and then use Altair [https://altair-viz.github.io/] to generate the Vega-Lite plots in Python. Then if you need to move to something besides Python to productionize, you can produce the same Vega-Lite definitions using the framework of your choice.
- FLaNK AI Weekly 18 March 2024
- FLaNK AI for 11 March 2024
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Vega-Altair: Declarative Visualization in Python
Feel free to open an issue to let us know which parts of the documentation you find obscure and if you have suggestions for how to improve them. We did a larger overhaul a few months back and are always open to feedback on how to improve it further! https://altair-viz.github.io/
(disclaimer: I'm a co-maintainer of Altair)
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Gnuplotlib: Non-Painful Plotting for NumPy
Vega-Altair is pretty great as well. It uses a grammar of graphics that’s slightly different from ggplot, but has most of the same advantages.
https://altair-viz.github.io/
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Altair - Declarative statistical visualization library for Python.
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Top 10 growing data visualization libraries in Python in 2023
Github: Altair
- What python library you are using for interactive visualisation?(other than plotly)
- Libs para gráficos
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If you had to pick a library from another language (Rust, JS, etc.) that isn’t currently available in Python and have it instantly converted into Python for you to use, what would it be?
Yeah, that's one of the main reasons I like altair. It has 10M downloads per month and the newest Git update is from two days ago.
What are some alternatives?
chdb - chDB is an embedded OLAP SQL Engine 🚀 powered by ClickHouse
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
deepeval - The LLM Evaluation Framework
bokeh - Interactive Data Visualization in the browser, from Python
super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
seaborn - Statistical data visualization in Python
starcoder - Home of StarCoder: fine-tuning & inference!
ggplot - ggplot port for python
open_model_zoo - Pre-trained Deep Learning models and demos (high quality and extremely fast)
plotnine - A Grammar of Graphics for Python
netron - Visualizer for neural network, deep learning and machine learning models
matplotlib - matplotlib: plotting with Python