river
orange
river | orange | |
---|---|---|
17 | 27 | |
4,775 | 4,611 | |
1.3% | 0.9% | |
9.1 | 9.6 | |
6 days ago | 9 days ago | |
Python | Python | |
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.
river
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🔍Underrated Open Source Projects You Should Know About 🧠
River is a Python library for online machine learning. Online machine learning can dynamically adapt to new patterns in the data, or when the data itself is generated as a function of time, e.g., stock price prediction, content personalization.
- Ask HN: What Underrated Open Source Project Deserves More Recognition?
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Unexpected Expected Thriller: A Tale of Coding Curiosity
Today, I'm going to take you on a thrilling coding adventure inspired by a LinkedIn code snippet, where I tangled with FastAPI, River, Watchdog, and Tenacity. Ready? Buckle up!
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Elevate Your Python Skills: Machine Learning Packages That Transformed My Journey as ML Engineer
Complimentary: river and skorch
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What are your favorite tools or components in the Kafka ecosystem?
River - https://github.com/online-ml/river (Online machine learning, best used with Bytewax for Kafka integration)
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Show HN: Want something better than k-means? Try BanditPAM
Hey, great work. Do you think this algorithm would be amenable to be done online? I'm the author of River (https://riverml.xyz) where we're looking for good online clustering algorithms.
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Python's “Disappointing” Superpowers
If you don't know Rust, but know Python, you can install Python libraries written in Rust with pip. Like, pip install polars or pip install robyn. In this case you follow the two bottom links. But then you don't write your own libraries and stuff so.. I guess that's not what you want.
But, if you want to learn Rust, you probably wouldn't start out with pyo3. You first install Rust with https://rustup.rs/ and then check out the official book, and the book rust by example, that you can find here https://www.rust-lang.org/learn - and maybe write some code on the Rust playground https://play.rust-lang.org/ - then, you use pyo3 to build Python libraries in Rust, and then use maturin https://www.maturin.rs/ to build and publish them to Pypi.
But if you still prefer to begin with Rust by writing Python libraries (it's a valid strategy if you are very comfortable with working with multiple stacks), the Maturin link has a tutorial that setups a program that is half written in python, half written in Rust, https://www.maturin.rs/tutorial.html (well the pyo3 link I sent also has one too. You should refer to the documentation of both, because you will use the two together)
After learning Rust, the next step is looking for libraries that you could leverage to make Python programs ultra fast. Here https://github.com/rayon-rs/rayon is an obvious choice, see some examples from the Rust cookbook https://rust-lang-nursery.github.io/rust-cookbook/concurrenc... - when you create a parallel iterator, it will distribute the processing to many threads (by default, one per core). The rust cookbook, by the way, is a nice reference to see the most used crates (Rust libraries) in the Rust ecosystem.
Anyway there are some posts about pyo3 on the web, like this blog post https://boring-guy.sh/posts/river-rust/ (note: it uses an outdated version of pyo3, and doesn't seem to use maturin which is a newer tool). This post was written by the developers of https://github.com/online-ml/river - another Python library written in Rust
- [D] Is it possible to update random forest parameters with new data instead of retraining on all data?
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If ChatGPT that could browse to the internet, what would you ask it to do?
Oh they definitely can be incrementally updated, there is just added complexity. Online learning has been used with more classical machine learning methods in real-time analytics for a while now. River is a library that handles that.
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[D] Good online learning-to-rank models
We have both bandits and FTRL implemented in River (https://riverml.xyz) if that helps.
orange
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Hierarchical Clustering
I know I've tooted its horn before, but Orange3 is a pretty neat Python-based GUI platform that makes this and a metric buttload of other statistical/ML techniques available to non-programmer types.
Just watch out for null character `x00` in the corpus. That always seems to kill it stone dead.
https://orangedatamining.com/
https://orange3.readthedocs.io/projects/orange-visual-progra...
- Orange Data Mining
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The Graph of Wikipedia [video]
For all you folks who aren't ace programmer types, the Orange3[1] platform gives you a very miniaturized[2] ability to turn out these sorts of visualizations very rapidly. It's not the most stable thing in the world, but the node-based ML workflow designer is worth the price of admission all by itself.
[1] https://orangedatamining.com/
[2] The Wikipedia extension in Text limits each search result to 25 articles, so sucking all of Wikipedia is . . well, Orange text analytics crashes when I look at it sideways with a null character, so let's not think about what would happen.
- Ask HN: What Underrated Open Source Project Deserves More Recognition?
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Taxonomy Management?
First is identifying the "similar" things in a corpus. Best way I know to do that, for non-programmer audiences, is the Orange Data Mining tool, which gives you a node-based text mining interface to perform statistical analysis on text. Hierarchical Clustering shows - very rapidly - how similar your "modules" are, which ones are most similar. There's many other techniques (semantic viewer, similarity hash, etc) as well - the right one will depend on how your content is laying about.
- Orange: Open-source machine learning and data visualization
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What exactly is AutoGPT?
Both tools are ripoffs of a data mining framework named Orange 3
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Why don't more people use Altair for python Visualizations instead of Plotly?
You should also check out Orange Data Mining, it allows to create a lot of charts, filter data from a chart to another, build ML models, predictions and a lot more. And you can do it with zero code.
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Advice on Transitioning to Data Science/ML/AI without Coding Experience
You can start with a free GUI based tool Orange. It is a component based data science workflow tool, which you can use to handle 60-75% of the traditional data science tasks from classification, regression, to basic neural networks.
- Has anybody used Orange?
What are some alternatives?
alibi-detect - Algorithms for outlier, adversarial and drift detection
glue - Linked Data Visualizations Across Multiple Files
python-tidal - Python API for TIDAL music streaming service
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
wayfire - A modular and extensible wayland compositor
RDKit - The official sources for the RDKit library
PySyft - Perform data science on data that remains in someone else's server
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
edl - Inofficial Qualcomm Firehose / Sahara / Streaming / Diag Tools :)
Interactive Parallel Computing with IPython - IPython Parallel: Interactive Parallel Computing in Python
makinage - Stream Processing Made Easy
NumPy - The fundamental package for scientific computing with Python.