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Top 15 C++ ML Projects
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MNN
MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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yggdrasil-decision-forests
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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vs-mlrt
Efficient CPU/GPU/Vulkan ML Runtimes for VapourSynth (with built-in support for waifu2x, DPIR, RealESRGANv2/v3, Real-CUGAN, RIFE, SCUNet, SwinIR and more!)
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tinymind
Tinymind is a Neural Network and Machine Learning project intended to provide a C++ template library for neural nets and machine learning algorithms within embedded systems.
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SaaSHub
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Project mention: TensorFlow-metal on Apple Mac is junk for training | news.ycombinator.com | 2024-01-16
Project mention: [D][R] Deploying deep models on memory constrained devices | /r/MachineLearning | 2023-10-03However, I am looking on this subject through the problem of training/finetuning deep models on the edge devices, being increasingly available thing to do. Looking at tflite, alibaba's MNN, mit-han-lab's tinyengine etc..
Yet another TEDIOUS BATTLE: Python vs. C++/C stack.
This project gained popularity due to the HIGH DEMAND for running large models with 1B+ parameters, like `llama`. Python dominates the interface and training ecosystem, but prior to llama.cpp, non-ML professionals showed little interest in a fast C++ interface library. While existing solutions like tensorflow-serving [1] in C++ were sufficiently fast with GPU support, llama.cpp took the initiative to optimize for CPU and trim unnecessary code, essentially code-golfing and sacrificing some algorithm correctness for improved performance, which isn't favored by "ML research".
NOTE: In my opinion, a true pioneer was DarkNet, which implemented the YOLO model series and significantly outperformed others [2]. Same trick basically like llama.cpp
[1] https://github.com/tensorflow/serving
Project mention: MatX: Efficient C++17 GPU numerical computing library with Python-like syntax | news.ycombinator.com | 2023-10-03I think a comparison to PyTorch, TensorFlow and/or JAX is more relevant than a comparison to CuPy/NumPy.
And then maybe also a comparison to Flashlight (https://github.com/flashlight/flashlight) or other C/C++ based ML/computing libraries?
Also, there is no mention of it, so I suppose this does not support automatic differentiation?
Project mention: Why do tree-based models still outperform deep learning on tabular data? (2022) | news.ycombinator.com | 2024-03-05Is it this library https://github.com/google/yggdrasil-decision-forests ?
Project mention: [D] Run Pytorch model inference on Microcontroller | /r/MachineLearning | 2023-11-14CMSIS-NN. ARM centric. Examples. They also have an example for a pytorch to tflite converter via onnx
Imagine you have an AI-powered personal alerting chat assistant that interacts using up-to-date data. Whether it's a big move in the stock market that affects your investments, any significant change on your shared SharePoint documents, or discounts on Amazon you were waiting for, the application is designed to keep you informed and alert you about any significant changes based on the criteria you set in advance using your natural language. In this post, we will learn how to build a full-stack event-driven weather alert chat application in Python using pretty cool tools: Streamlit, NATS, and OpenAI. The app can collect real-time weather information, understand your criteria for alerts using AI, and deliver these alerts to the user interface.
or whatever you want, you need to write the code yourself though. https://github.com/AmusementClub/vs-mlrt
Project mention: MIT 6.5940: TinyML and Efficient Deep Learning Computing | news.ycombinator.com | 2023-09-28These TinyML courses on edx look good https://www.edx.org/professional-certificate/harvardx-tiny-m...
Project mention: Is there anything like Embedded Artificial Intelligence & Machine Learning? Can anyone tell me more about it? | /r/embedded | 2023-12-07Take a look at TinyMind: https://github.com/danmcleran/tinymind
C++ ML related posts
- Why do tree-based models still outperform deep learning on tabular data? (2022)
- MIT 6.5940: TinyML and Efficient Deep Learning Computing
- I was just wondering, with all the hype and latest advance in AI, is there something like AI embedded systems? Like deploying state-of-the-art AI models on embedded systems.
- Show HN: Polymath: Convert any music-library into a sample-library with ML
- OneFlow v0.9.0 Came Out!——A Distributed Deep Learning Framework
- OneFlow v0.9.0 Came Out!
- [P] Probably the Fastest Open Source Stable Diffusion is released
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A note from our sponsor - SaaSHub
www.saashub.com | 25 Apr 2024
Index
What are some of the best open-source ML projects in C++? This list will help you:
Project | Stars | |
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1 | tensorflow | 182,456 |
2 | MNN | 8,293 |
3 | serving | 6,071 |
4 | oneflow | 5,721 |
5 | flashlight | 5,145 |
6 | yggdrasil-decision-forests | 423 |
7 | ML-examples | 404 |
8 | ecole | 296 |
9 | liboai | 291 |
10 | rb-libsvm | 278 |
11 | vs-mlrt | 230 |
12 | arduino-library | 38 |
13 | PyHook | 23 |
14 | CuProphet | 8 |
15 | tinymind | 7 |
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