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Top 23 C++ Machine Learning Projects
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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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openpose
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
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C-Plus-Plus
Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.
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xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
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DeepSpeech
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
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PaddlePaddle
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
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LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
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vowpal_wabbit
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
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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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jetson-inference
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
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# L2-normalize the encoding tensors image_encoding = tf.math.l2_normalize(image_encoding, axis=1) audio_encoding = tf.math.l2_normalize(audio_encoding, axis=1) # Find euclidean distance between image_encoding and audio_encoding # Essentially trying to detect if the face is saying the audio # Will return nan without the 1e-12 offset due to https://github.com/tensorflow/tensorflow/issues/12071 d = tf.norm((image_encoding - audio_encoding) + 1e-12, ord='euclidean', axis=1, keepdims=True) discriminator = keras.Model(inputs=[image_input, audio_input], outputs=[d], name="discriminator")
We are going to be using an OCR (Optical Character Recognition) engine called Tesseract for the image-to-text recognition part. It is free software, released under the Apache License. Install the engine for your desired OS from their official website. I'm using Windows for this. Add the installation path to your environment variables.
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Project mention: AI "Artists" Are Lazy, and the Ultimate Goal of AI Image Generation (hint: its sloth) | /r/ArtistHate | 2023-11-25Open Pose, a multi-person keypoint detection library for body, face, hands, and foot estimation [10], is used for posing generated characters;
Project mention: stackgbm VS xgboost - a user suggested alternative | libhunt.com/r/stackgbm | 2024-05-05
mediapipe/docs/solutions/pose.md at master · google/mediapipe · GitHub
Project mention: ESpeak-ng: speech synthesizer with more than one hundred languages and accents | news.ycombinator.com | 2024-05-01As I understand it DeepSpeech is no longer actively maintained by Mozilla: https://github.com/mozilla/DeepSpeech/issues/3693
For Text To Speech, I've found Piper TTS useful (for situations where "quality"=="realistic"/"natual"): https://github.com/rhasspy/piper
For Speech to Text (which AIUI DeepSpeech provided), I've had some success with Vosk: https://github.com/alphacep/vosk-api
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Project mention: SIRUS.jl: Interpretable Machine Learning via Rule Extraction | /r/Julia | 2023-06-29SIRUS.jl is a pure Julia implementation of the SIRUS algorithm by Bénard et al. (2021). The algorithm is a rule-based machine learning model meaning that it is fully interpretable. The algorithm does this by firstly fitting a random forests and then converting this forest to rules. Furthermore, the algorithm is stable and achieves a predictive performance that is comparable to LightGBM, a state-of-the-art gradient boosting model created by Microsoft. Interpretability, stability, and predictive performance are described in more detail below.
Project mention: Modern Image Processing Algorithms Implementation in C | news.ycombinator.com | 2023-06-06
ONNX Runtime: ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Project mention: Does anyone else agree that the links to the latest development version of Open3D don't work? | /r/cscareerquestions | 2023-07-10I was going to file a bug about another issue, but I have to download the development version. This is why I want this solved quickly. None of the links seem to work: https://github.com/isl-org/Open3D/issues/6259
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: Grafana Beyla: OSS eBPF auto-instrumentation for application observability | news.ycombinator.com | 2023-09-13
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?
C++ Machine Learning related posts
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stackgbm VS xgboost - a user suggested alternative
2 projects | 5 May 2024 -
msaenet VS glmnet - a user suggested alternative
2 projects | 5 May 2024 -
OpenMLDB v0.9.0 Release: Major Upgrade in SQL Capabilities Covering the Entire Feature Servicing Process
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Side Quest Devblog #1: These Fakes are getting Deep
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Google lays off its Python team
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Show HN: I ported Suno AI's Bark model in C for fast realistic audio generation
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Supabase Storage: now supports the S3 protocol
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A note from our sponsor - SaaSHub
www.saashub.com | 5 May 2024
Index
What are some of the best open-source Machine Learning projects in C++? This list will help you:
Project | Stars | |
---|---|---|
1 | tensorflow | 182,575 |
2 | tesseract-ocr | 58,182 |
3 | Caffe | 33,875 |
4 | openpose | 29,902 |
5 | C-Plus-Plus | 29,161 |
6 | xgboost | 25,595 |
7 | mediapipe | 25,528 |
8 | DeepSpeech | 24,324 |
9 | PaddlePaddle | 21,625 |
10 | CNTK | 17,435 |
11 | LightGBM | 16,057 |
12 | Dlib | 13,031 |
13 | onnxruntime | 12,736 |
14 | Open3D | 10,514 |
15 | vowpal_wabbit | 8,403 |
16 | MNN | 8,313 |
17 | jetson-inference | 7,349 |
18 | serving | 6,079 |
19 | interpret | 6,007 |
20 | tiny-cnn | 5,763 |
21 | oneflow | 5,726 |
22 | pixie | 5,285 |
23 | flashlight | 5,159 |
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