pyDenStream
orange
Our great sponsors
pyDenStream | orange | |
---|---|---|
1 | 27 | |
9 | 4,604 | |
- | 1.7% | |
5.2 | 9.6 | |
about 2 months ago | 9 days ago | |
Python | Python | |
- |
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.
pyDenStream
-
[P] Implementation of DenStream
The implementation can be found here: https://github.com/MrParosk/pyDenStream
orange
-
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
-
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?
-
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
-
What exactly is AutoGPT?
Both tools are ripoffs of a data mining framework named Orange 3
-
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.
-
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?
stringlifier - Stringlifier is on Opensource ML Library for detecting random strings in raw text. It can be used in sanitising logs, detecting accidentally exposed credentials and as a pre-processing step in unsupervised ML-based analysis of application text data.
glue - Linked Data Visualizations Across Multiple Files
uis-rnn - This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.
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
dedupe - :id: A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.
RDKit - The official sources for the RDKit library
impfuzzy - Fuzzy Hash calculated from import API of PE files
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
hazelcast-python-client - Hazelcast Python Client
Interactive Parallel Computing with IPython - IPython Parallel: Interactive Parallel Computing in Python
NumPy - The fundamental package for scientific computing with Python.
Dask - Parallel computing with task scheduling