Simple machine learning tool in Python (>=3.7) computing an anomaly score of seismic waveform amplitudes. By using a pre-trained Isolation forest model, the program can be used for identification of outliers in
changes in particular are important. One is the addition of thekeyparameter to theInputelement and one of theTextelements. Akeyis like a name for an element. Or, in Python terms, it's like a dictionary key. TheInputelement's key will be used as a dictionary key later in the code. ...
P. Machine Learning: A Probabilistic Perspective (MIT Press, 2012). Lecun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015). Article CAS PubMed Google Scholar Seabold, S. & Perktold, J. Statsmodels: econometric and statistical modeling with Python. Proc. 9th...
Today, we’re excited to announce the release of SynapseML (previously MMLSpark), an open-source library that simplifies the creation of massively scalable machine learning (ML) pipelines. Building production-ready distributed ML pipelines can be difficult, even for the most seasoned de...
While there are a few machine learning libraries out there, PyBrain aims to be a very easy-to-use modular library that can be used by entry-level students but still offers the flexibility and algorithms for state-of-the-art research. ...
A Simple High Performance Compututing Framework for [Federated] Machine Learning 展开 收起 暂无标签 README Apache-2.0 使用Apache-2.0 开源许可协议 Code of conduct 23 Stars 7 Watching 3 Forks 保存更改 取消 发行版 暂无发行版 eggroll 开源评估指数 开源评估指数源自 OSS-Compass 评估体系...
With Gluon, you can build machine learning models using a simple Python API and a range of pre-built, optimized neural network components. This makes it easy to build neural networks using simple code without sacrificing training performance. Gluon makes building new computer vision models...
productionizing machine learning models written in R and Python were problematic due to limited hosting options. The rest of endjin's content platform is built using PaaS and Serverless components, so the combination of ML.NET and Azure Functions was incredibly appealing to the company; as soon ...
With Gluon, you can build machine learning models using a simple Python API and a range of pre-built, optimized neural network components. This makes it easy to build neural networks using simple code without sacrificing training performance. Gluon makes building new computer vision models...
If a call to the training or prediction functions of a machine learning library instead yields unexpected exceptions, this is a clear indicator of a bug in the most crucial functions. We developed a set of smoke tests that we believe all machine learning algorithms must be able to pass. The...