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 semismic data, assign robustness weights, o
Bare bone examples of machine learning in TensorFlow big-datasimpletensorflowlinear-regressiondistributed-computingtensorflow-tutorialstensorflow-exercisestensorflow-examples UpdatedMar 14, 2017 Python A maroto way to create PDFs. Maroto is inspired in Bootstrap and uses gofpdf. Fast and simple. ...
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...
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Understanding signal processing helps algorithm developers analyze and manipulate raw data, improving accuracy in fields like machine learning, computer vision, and real-time data applications. Specialization in algorithm development You’ll find more than one way to use algorithms in development. Many av...
Bio:Dr. Michael J. Garbadeis the founder and CEO of Los Angeles-based blockchain education companyLiveEdu. It’s the world’s leading platform that equips people with practical skills on creating complete products in future technological fields, including machine learning. ...
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...
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 ...
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...
or identify patterns in code or data, produce insights or correlations, or make predictions, recommendations, or decisions; in each case, where the system or model operates using machine learning, neural networks, large language models, ...