emlearn
Shynet
emlearn | Shynet | |
---|---|---|
5 | 21 | |
424 | 2,815 | |
15.1% | - | |
9.2 | 6.7 | |
9 days ago | 22 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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.
emlearn
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EleutherAI announces it has become a non-profit
> My big gripe, and for obvious reasons, is that we need to step away from cloud-based inference, and it doesn't seem like anyone's working on that.
I think there are steps being taken in this direction (check out [1] and [2] for interesting lightweight transpile / ad-hoc training projects) but there is a lack of centralized community for these constrained problems.
[1] https://github.com/emlearn/emlearn
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Simple and embedded friendly C code for Machine Learning inference algorithms
Examples: Gaussian Mixture Models (GMM) for anomaly detection or clustering Mahalanobis distance (EllipticEnvelope) for anomaly detection Decision trees and tree ensembles (Random Forest, ExtraTrees) Feed-forward Neural Networks (Multilayer Perceptron, MLP) for classification Gaussian Naive Bayes for classification
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[D] Drop your best open source Deep learning related Project
https://github.com/emlearn/emlearn is a ML inference engine for microcontrollers and embedded systems, allowing to deploy models to any platform with a C99 compiler. Has also been used for network traffic analysis as a Linux kernel module, and embedded in Android apps.
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Regression with the C64
The C64 has 64 kB of RAM. That is more than many contemporary microcontrollers. Using something like https://github.com/emlearn/emlearn allows to generate portable C code of ML models for such targets. Should be able to classify digits (MNIST) no problem on such hardware. Assuming there is a workable C compiler available.
Disclosure: Maintainer of emlearn project.
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Ask HN: What are some tools / libraries you built yourself?
I built emlearn, a Machine Learning inference engine for microcontrollers and embedded systems. It allows converting traditional ML models to simple and portable C99, following best practices in embedded software (no dynamic allocations etc). https://github.com/emlearn/emlearn
Shynet
- Shynet: Modern, privacy-friendly, web analytics, without cookies or JavaScript
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It Took Me a Decade to Find the Perfect Personal Website Stack – Ghost+Fathom
+1 on shynet! I use it for my personal website and my blog, and it's been working great.
I got it up and running with Podman, so no need to install and run the Docker daemon. I also fixed SQLite support [1], so no need for an additional DB server.
I analyzed available open-source web analytics tools [2] and AFAIK there is simpler solution for web analytics that doesn't involve a third party.
[1] https://github.com/milesmcc/shynet/issues/208
[2] https://blog.fidelramos.net/software/privacy-respecting-self...
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Recommendations for self-hosted Google Analytics alternatives?
I like shynet
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Ask HN: Any alternatives to Google Analytics that don't require cookies?
I am using shynet for a while now. Really all I need to know :)
https://github.com/milesmcc/shynet
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Why you should remove Google Analytics from your website
There's also Shynet.
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Show HN: Sudopad – Private link sharing board for friends
Oh that is actually shynet self hosted analytics which is privacy friendly. https://github.com/milesmcc/shynet
But I think I'll just remove it for now.
- Please name some open source projects which are collecting small user analytics metrics and how
- Google Analytics declared illegal in the EU.
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Ask HN: Good open source alternatives to Google Analytics?
Shynet: https://github.com/milesmcc/shynet
The goal is to provide, privacy-friendly, and detailed web analytics that works without cookies or JS. And it's completely open source.
Full disclosure: I am the primary maintainer.
What are some alternatives?
miceforest - Multiple Imputation with LightGBM in Python
Plausible Analytics - Simple, open source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics.
cppflow - Run TensorFlow models in C++ without installation and without Bazel
Umami - Umami is a simple, fast, privacy-focused alternative to Google Analytics.
fselect - Find files with SQL-like queries
Open Web Analytics - Official repository for Open Web Analytics which is an open source alternative to commercial tools such as Google Analytics. Stay in control of the data you collect about the use of your website or app. Please consider sponsoring this project.
pico-wake-word - MicroSpeech Wake Word example on the Raspberry Pi Pico. This is a port of the example on the TensorFlow repository.
flask-profiler - a flask profiler which watches endpoint calls and tries to make some analysis.
sklearn-project-template - Machine learning template for projects based on sklearn library.
Matomo - Empowering People Ethically with the leading open source alternative to Google Analytics that gives you full control over your data. Matomo lets you easily collect data from websites & apps and visualise this data and extract insights. Privacy is built-in. Liberating Web Analytics. Star us on Github? +1. And we love Pull Requests!
experta - Expert Systems for Python
GoatCounter - Easy web analytics. No tracking of personal data.