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Based on our record, Scikit-learn should be more popular than Extism. It has been mentiond 31 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 11 months ago
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / about 1 year ago
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / almost 2 years ago
I started using WebAssembly in earnest a few months ago to make a backend auth library that works in several different languages[0]. It's built on Extism[1], which abstracts away some of the interfacing complexity. It's been an awesome experience. Frequently feels like magic. WASM is in an interesting place. The value has clearly been proved with a pretty minimal core spec. Now there's a big push to implement a... - Source: Hacker News / about 1 month ago
Application plugins could also be wasm. That lets plugin authors write in any language they want and have their plugin work. That's the idea behind the Extism framework: https://extism.org/. - Source: Hacker News / 3 months ago
The WebAssembly component model is aimed at having composable components that can call each other. The components can be written in any language, compiled to WebAssembly, and interoperate: https://github.com/WebAssembly/component-model/ https://github.com/extism/extism A project to bring WebAssembly plugins to Godot: https://github.com/ashtonmeuser/godot-wasm Wasmer can be embedded in applications:... - Source: Hacker News / 4 months ago
This is exactly what we created Extism[0] and XTP[1] for! [0]: https://extism.org. - Source: Hacker News / 7 months ago
This is an exciting option as it provides a sandboxed environment to run code. One caveat is that you need an environment with Javascript bindings. However, an interesting project called Extism facilitates that. You might want to follow their tutorial. - Source: dev.to / 10 months ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
OpenCL - Application and Data, Languages & Frameworks, and Language Extensions
OpenCV - OpenCV is the world's biggest computer vision library
Wasmer - The Universal WebAssembly Runtime
NumPy - NumPy is the fundamental package for scientific computing with Python
Docker Compose - Define and run multi-container applications with Docker