quant-portfolio-visualizer
orange
| quant-portfolio-visualizer | orange | |
|---|---|---|
| 1 | 27 | |
| 8 | 4,626 | |
| - | 1.2% | |
| 8.9 | 9.6 | |
| 2 months ago | 3 days ago | |
| Python | Python | |
| - | GNU General Public License v3.0 or later |
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quant-portfolio-visualizer
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Just came across a thread on how to use an open source Bloomberg terminal. Thought it might interest some apes who ca’t afford the 24k terminal
Ha! Here's the link to pyquant from op. https://github.com/eshinhw/pyQuant
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?
glue - Linked Data Visualizations Across Multiple Files
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
RDKit - The official sources for the RDKit library
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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
Neupy - NeuPy is a Tensorflow based python library for prototyping and building neural networks
docker-data-science - Docker image with Data Science tools.
SciPy - SciPy library main repository
statsmodels - Statsmodels: statistical modeling and econometrics in Python
bcbio-nextgen - Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis