Αποτελέσματα Αναζήτησης
21 Δεκ 2017 · The more reliable and way more flexible way is to do the prediction in Python using sklearn and communicate with your C# program via files or (better) a web service. Olivier Grisel (one of the sklearn authors) concisely describes your options in this post.
4 Οκτ 2024 · Take this example– you want to leverage a Python library to analyse some data using an ML algorithm like K-Means. You have lots of options in Python, like scikit-learn, TensorFlow, PyTorch, etc. You select scikit-learn because it’s easy to use and doesn’t have too many dependencies.
4 Ιουλ 2020 · In this article, we’ll look at a better way to bridge the technology gap between Data Scientists and App Developers using the ONNX Model format and the ONNX Runtime. Specifically, we’ll show how you can build and train a model using Sci-kit Learn, then use that same model to perform real-time inference in a .NET Core Web API.
4 Σεπ 2024 · Scikit-learn has emerged as a powerful and user-friendly Python library. Its simplicity and versatility make it a better choice for both beginners and seasoned data scientists to build and implement machine learning models. In this article, we will explore about Sklearn.
5 Απρ 2022 · To deploy a machine learning trained model in a .NET application using ONNX files, the sklearn model is converted into a serialized string with the assistance of the skl2onnx library. Here ...
This repo contains many practical examples written in SciSharp's machine learning libraries. If you still don't know how to use .NET for deep learning, getting started from these examples is your best choice. Requirements: Run specific example in shell: :: run specific example .
Machine Learning in .NET Core. Contribute to SciSharp/scikit-learn.net development by creating an account on GitHub.
