mlpack
Caffe
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mlpack | Caffe | |
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4 | 6 | |
4,787 | 33,837 | |
2.0% | 0.2% | |
9.9 | 0.0 | |
5 days ago | about 2 months ago | |
C++ | C++ | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
mlpack
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How much C++ is used when it comes to performing quant research?
Does C++ have the equivalent of Pandas or Apache Spark? Are there extensive libraries that exist/are being developed that allow you to perform operations with data? Or do people just use a combination of Python & its various libraries (NumPy etc)? If we leave aside the data bit, are there libraries that allow you to develop ML models in C++ (mlpack for instance ) faster & more efficiently compared to their Python counterparts (scikit-learn)? On a more general note, how does C++ fit into the routine of a Quant Researcher? And at what scale does an organization decide they need to start switching to other languages and spend more time developing the code ?
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What is the most used library for AI in C++ ?
mlpack is a great library for machine learning in C++. It's very fast and not too much of a learning curve.
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Ensmallen: A C++ Library for Efficient Numerical Optimization
This toolkit was originally part of the mlpack machine learning library (https://github.com/mlpack/mlpack) before it was split out into a separate, standalone effort.
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Top 10 Python Libraries for Machine Learning
Github Repository: https://github.com/mlpack/mlpack Developed By: Community, supported by Georgia Institute of technology Primary purpose: Multiple ML Models and Algorithms
Caffe
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List of AI-Models
Click to Learn more...
- Caffe | Deep Learning Framework
- German ad: "Artificial intelligence: the 4 most used drinks will be placed on the main screen"
- How do I install Caffe framework on Mac M1?
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Una corta intro a las Redes Neuronales Artificiales
Caffe de BAIR
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Can someone please guide me regarding these different face detection models?
Caffe is a DL framework just like TensorFlow, PyTorch etc. OpenPose is a real-time person detection library, implemented in Caffe and c++. You can find the original paper here and the implementation here.
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
Caffe2
Dlib - A toolkit for making real world machine learning and data analysis applications in C++
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
SHOGUN - Shōgun
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
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
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
examples - TensorFlow examples
Porcupine - On-device wake word detection powered by deep learning