ydata-profiling
label-studio
ydata-profiling | label-studio | |
---|---|---|
43 | 50 | |
12,053 | 16,546 | |
0.9% | 2.5% | |
8.5 | 9.8 | |
10 days ago | 3 days ago | |
Python | JavaScript | |
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.
ydata-profiling
- FLaNK 25 December 2023
-
First 15 Open Source Advent projects
6. Ydata-synthetic and Ydata-profiling by YData | Github | tutorial
-
Coding Wonderland: Contribute to YData Profiling and YData Synthetic in this Advent of Code
Send us your North ⭐️: "On the first day of Christmas, my true contributor gave to me..." a star in my GitHub tree! 🎵 If you love these projects too, star ydata-profiling or ydata-synthetic and let your friends know why you love it so much!
- Data exploration is not dead
- Explore your data in a single line of code
-
Which preprocessing steps to improve the performance of a naive bayes classifier
My suggestion start with the EDA - there are a lot of packages that automate that for you already. My usual go-to: https://github.com/ydataai/ydata-profiling.
-
Simulating sales data
If you're not sure about the behaviour of your data (i.e., if the original data has properties like seasonality), you can use ydata-profiling to profile your data first.
-
I recorded a Data Science Project using Python and uploaded it on Youtube
Super cool! For EDA, you could give ydata-profiling a spin sometime and speed up the process!
-
Ydata-Profiling and Dask
Hey guys,
We've been recently at the Dask Demo Day and we're hoping to launch a new feature on ydata-profiling, with the support for Dask dataframes!
We're looking for Dask Wizards to start collaborating on this feature, so if you're interested, please join us to define the roadmap of the project and start making it real
Current GitHub branch is here: https://github.com/ydataai/ydata-profiling/tree/feat/dask
Dedicated dask channel here: https://discord.gg/EHDBuSSDuy
-
🧠 ydata-profiling + Dask!
We're looking for Dask Wizards 🧙🏻♂️ to start collaborating on this branch, so if you're interested, please join us to define the roadmap of the project and start making it real 🚀
label-studio
-
Annotation is dead
If instead you have a cohort on hand — -i.e., you do not want to send your data to a third party for any reason, or perhaps you have energetic undergrads — -then you could alternatively consider local, open-source annotation such as CVAT and Label Studio. Finally, nowadays, you might instead work with Large Multimodal Models to have them annotate your data; more on this awkward angle later.
-
First 15 Open Source Advent projects
14. LabelStudio by Human Signal | Github | tutorial
-
Exploring Open-Source Alternatives to Landing AI for Robust MLOps
For instance, the COCO Annotator is a web-based image annotation tool tailored for the COCO dataset format, allowing collaborative labeling with features like attribute tagging and automatic segmentation. Similarly, Label Studio offers an easy-to-use interface for bounding box object labeling in images.
- FLaNK Stack Weekly for 14 Aug 2023
-
You Can't Have a Free Software AI Stack
Huh?
I wrote my own system for classifying a stream of texts in Python, I might Open Source it one of these days but I have to get it to the point where it is modular enough that I can customize it to do the particular things I want without subjecting people to my whims... I use it every day and I'm not afraid to demo it because it is rock solid.
My understanding is that my system would not be hard to adapt to work on images for certain kinds of tasks.
Pytorch is open source, Huggingface is open source. CUDA isn't. This is
https://labelstud.io/
and for annotating text spans there are so many open source tools
https://github.com/doccano/doccano
I worked for a company a few years back that built annotation tools for projects we sold to customers but never quite got to a polished general purpose annotator. Today there are an overwhelming number of companies in this space and products I never heard of, many of which are cloud based or paid. Looks like a gold rush to me.
- Label Studio: Open-Source Data Labeling Platform
-
Best (quickest) way to annotate images for whole-image classification?
LabelStudio is free for single use. https://labelstud.io/
- Label Studio – Free multi-type data ML labeling and annotation tool
-
Way to label yolov7 images fast
LabelStudio is pretty nice, and free & open source, but I have yet to try out their ML integration with a YOLO object detection model.
-
image labeling online Tools
Label Studio is an open source data labeling tool that includes annotation functionality. It provides a simple user interface (UI) that lets you label various data types, including text, audio, time series data, videos, and images, and export the information to various model formats.
What are some alternatives?
dtale - Visualizer for pandas data structures
cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]
DataProfiler - What's in your data? Extract schema, statistics and entities from datasets
doccano - Open source annotation tool for machine learning practitioners.
dataframe-go - DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration
awesome-data-labeling - A curated list of awesome data labeling tools
lux - Automatically visualize your pandas dataframe via a single print! 📊 💡
diffgram - The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.
get-started-with-JAX - The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
labelbox-custom-labeling-apps - Explore example custom labeling apps built with Labelbox SDK