autokeras
mike
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| autokeras | mike | |
|---|---|---|
| 5 | 2 | |
| 9,066 | 465 | |
| 0.2% | - | |
| 5.3 | 7.4 | |
| about 1 month ago | 21 days ago | |
| Python | Python | |
| Apache License 2.0 | 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.
autokeras
- Machine Learning Algorithms Cheat Sheet
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Ask HN: Which piece of tech is underutilized?
I think the interfaces aren't high level enough for the average programmer to adopt it. It needs what https://autokeras.com is for neural nets.
- Technical documentation that just works
- SVM training taking forever on my local machine. Will using AWS Sagemaker be faster for training SVM (Linear) models?
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[D] [P] How do you use tools like AutoML?
AutoKeras time_series_forecaster.py
mike
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where do you host your embedded docs?
I use MkDocs for generating the documentation website (using the Material theme) and host in on GitHub pages. For managing and hosting multiple versions, I use the Mike extension for MkDocs.
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Technical documentation that just works
Thanks. This is an alternative vision compared with what I am doing, but it seems better. Especially the C4 model as basic philosophy, and then the supporting technology.
Pleas blog about this, it is very interesting to me.
Just to be sure: this is what you mean with Mike?
https://github.com/jimporter/mike
What are some alternatives?
autogluon - AutoGluon: Fast and Accurate ML in 3 Lines of Code
mkdocs-material - Documentation that simply works
mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
docs - The official Pi-hole documentation
adanet - Fast and flexible AutoML with learning guarantees.
sphinx - The Sphinx documentation generator
tf-keras-vis - Neural network visualization toolkit for tf.keras
furo - A clean customizable documentation theme for Sphinx
automlbenchmark - OpenML AutoML Benchmarking Framework
kotlin4example - Literate programming for Kotlin. Write markdown based documentation for your kotlin project with working examples.
AutoViz - Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
mkdocstrings - :blue_book: Automatic documentation from sources, for MkDocs.