-
OPT-NC
- Nouméa, New-Caledonia
-
23:10
(UTC -12:00) - https://dev.to/adriens
- @rastadidi
- @devopslabs2812
- https://www.kaggle.com/adriensales
- in/adrien-sales
🧑🔬 Datascience
PyGWalker: Turn your dataframe into an interactive UI for visual analysis
Streamlit — A faster way to build and share data apps.
Voilà turns Jupyter notebooks into standalone web applications
LangChain4j is an open-source Java library that simplifies the integration of LLMs into Java applications through a unified API, providing access to popular LLMs and vector databases. It makes impl…
An open-source, low-code machine learning library in Python
PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer
GPU-accelerated force graph layout and rendering
Tooling for the archive created by Garmin datamanagement.
Turns Data and AI algorithms into production-ready web applications in no time.
An open source alternative to Tableau. Embeddable visual analytic
Data validation using Python type hints
Scratch is a swiss army knife for big data.
A high-level plotting API for pandas, dask, xarray, and networkx built on HoloViews
Quickly and accurately render even the largest data.
Interactive Data Visualization in the browser, from Python
AI code-writing assistant that understands data content
data load tool (dlt) is an open source Python library that makes data loading easy 🛠️
Apache Superset is a Data Visualization and Data Exploration Platform
Jupyter notebooks that support my graph data science blog posts at https://bratanic-tomaz.medium.com/
🦆 A curated list of awesome DuckDB resources
Creating beautiful plots of data maps
Business intelligence as code: build fast, interactive data visualizations in SQL and markdown
Extract place names from a URL or text, and add context to those names -- for example distinguishing between a country, region or city.
Apache Spark - A unified analytics engine for large-scale data processing
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️





