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Based on our record, Pandas seems to be a lot more popular than Extism. While we know about 219 links to Pandas, we've tracked only 19 mentions of Extism. 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.
Libraries for data science and deep learning that are always changing. - Source: dev.to / 14 days ago
# Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / 30 days ago
As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / about 1 month ago
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
This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 9 months 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 2 months 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 / 5 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
NumPy - NumPy is the fundamental package for scientific computing with Python
OpenCL - Application and Data, Languages & Frameworks, and Language Extensions
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
OpenCV - OpenCV is the world's biggest computer vision library
Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.
Kata Containers - Lightweight virtual machines that seamlessly plug into the containers ecosystem.