lightwood
Lightwood is Legos for Machine Learning. (by mindsdb)
pyprobml
Python code for "Probabilistic Machine learning" book by Kevin Murphy (by probml)
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| lightwood | pyprobml | |
|---|---|---|
| 2 | 3 | |
| 420 | 6,243 | |
| 3.8% | 1.1% | |
| 9.2 | 6.2 | |
| 8 days ago | 4 months ago | |
| Python | Jupyter Notebook | |
| GNU General Public License v3.0 only | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
lightwood
Posts with mentions or reviews of lightwood.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-02-19.
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[D] What would a good ML take home test look like for you?
Create a very detailed issue about this (bonus points, you can use the same thing for all candidates to have a fair evaluation). Here's an example.
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Launch HN: MindsDB (YC W20) – Machine Learning Inside Your Database
3. A decoder that is trained to generate images takes that representation and generates an image1.
Note: above is a good illustrative example, in practice, we're good with outputting dates, numerical, categories, tags and time-series (i.e. predicting 20 steps ahead). We haven't put much work into image/text/audio/video outputs
You should be able to find more details about how we do this in the docs and most of the heavy lifting happens in the lightwood repo, the code for that is fairly readable I hope: https://github.com/mindsdb/lightwood
pyprobml
Posts with mentions or reviews of pyprobml.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-05-09.
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Best Possible Book Recommended for Machine Learning [Discussion] [D] [Recommendation]
Another great book is Kevin Murphy’s Machine Learning: A probabilistic approach. He just launched the second version of his book and he has a Python repo for the models and graphs: https://github.com/probml/pyprobml
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Probabilistic Machine Learning, Kevin Murphy (2nd edition, 2021)
This exists actually, it's not complete yet (I think?) but it covers a lot of the material in the book:
What are some alternatives?
When comparing lightwood and pyprobml you can also consider the following projects:
MindsDB - The platform for customizing AI from enterprise data
numpyro - Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.