deodel
A mixed attributes predictive algorithm implemented in Python. (by c4pub)
awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning (by EthicalML)
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| deodel | awesome-production-machine-learning | |
|---|---|---|
| 13 | 9 | |
| 5 | 15,947 | |
| - | 2.1% | |
| 6.3 | 7.4 | |
| 2 months ago | 7 days ago | |
| Python | ||
| - | 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.
deodel
Posts with mentions or reviews of deodel.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-17.
- [P] New predictor does classification intermixed with regression
- Easy Machine Learning Dataset Evaluation Tool (Update)
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What are some practical tips for efficiently handling missing or null values in datasets during data analysis in Python?
You could use this new classifier deodel that is very robust. It deals seamlessly with missing data, nulls, mixed numerical and categorical attributes, and multi-class targets. You can see an application with this tool:
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What’s your approach to highly imbalanced data sets?
Just to mention that there is also a new algorithm that is immune to the imbalance of data. An implementation in python is available at: - https://github.com/c4pub/deodel
- Robust mixed attributes classifier (machine learning)
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[P] We are building a curated list of open source tooling for data-centric AI workflows, looking for contributions.
The deodel classifier can act as a quick dataset evaluation tool. If your data is available in table format, you can check its potential for prediction/classification. Just feed it to deodel. It accepts mixed attributes without any preliminary curation. It simply considers attribute values expressed as floats (dot decimal) as being continuous. It accepts even a mix of continuous and categorical values for the same attribute column.
- [D] Open-source package to mix numerical, categorical and text features?
- [P] Discretization: equal-width trumps equal-frequency?
- [P] Discretization: equal-width beats equal-frequency?
awesome-production-machine-learning
Posts with mentions or reviews of awesome-production-machine-learning.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-13.
-
Exploring Open-Source Alternatives to Landing AI for Robust MLOps
One trove of treasures is the awesome-production-machine-learning repository on GitHub. This curated list provides a multitude of frameworks, libraries, and software designed to facilitate various stages of the ML lifecycle.
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[P] We are building a curated list of open source tooling for data-centric AI workflows, looking for contributions.
There is a cool, gigantic list for MLOps that I can recommend: https://github.com/EthicalML/awesome-production-machine-learning
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How much of a full DS project pipeline can I do for free?
There are a lot of frameworks and specific tools out there that try to make production ML projects viable; from specific like Airflow (orchestrating jobs) and MLflow (experiment tracking) to more complex ones like Kubeflow. You can have a grasp here.
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Sqldiff: SQLite Database Difference Utility
https://github.com/EthicalML/awesome-production-machine-lear...
- [D] What are the best resources to crack M L system design interviews?
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I'm looking for a tool that let's you visualize the models architecture like this. Any idea what it is called?
https://github.com/EthicalML/awesome-production-machine-learning I think you will find most of the tools to visualize the model on this link.
- Awesome production machine learning - curated list of awesome open source libraries that will help you deploy, monitor, version, scale, and secure your production machine learning [free] [website] [@all]
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Crucial differences in MLOps for deep learning
2/ https://github.com/EthicalML/awesome-production-machine-learning
What are some alternatives?
When comparing deodel and awesome-production-machine-learning you can also consider the following projects:
dgl - Python package built to ease deep learning on graph, on top of existing DL frameworks.
shap - A game theoretic approach to explain the output of any machine learning model.
BotLibre - An open platform for artificial intelligence, chat bots, virtual agents, social media automation, and live chat automation.
awesome-jax - JAX - A curated list of resources https://github.com/google/jax
grape - 🍇 GRAPE is a Rust/Python Graph Representation Learning library for Predictions and Evaluations
netron - Visualizer for neural network, deep learning and machine learning models
ydata-synthetic - Synthetic data generators for tabular and time-series data
awesome-mlops - :sunglasses: A curated list of awesome MLOps tools
misc
awesome-ml-for-cybersecurity - :octocat: Machine Learning for Cyber Security
general_class_balancer - Data matching algorithm for categorical and continuous variables
datascience - Curated list of Python resources for data science.
deodel vs dgl
awesome-production-machine-learning vs shap
deodel vs BotLibre
awesome-production-machine-learning vs awesome-jax
deodel vs grape
awesome-production-machine-learning vs netron
deodel vs ydata-synthetic
awesome-production-machine-learning vs awesome-mlops
deodel vs misc
awesome-production-machine-learning vs awesome-ml-for-cybersecurity
deodel vs general_class_balancer
awesome-production-machine-learning vs datascience