nuitka might be a bit more popular than Scikit-learn. We know about 36 links to it since March 2021 and only 28 links to Scikit-learn. 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.
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 / 2 months 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 / 11 months ago
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
This is a good place to mention https://nuitka.net/ which aims to compile python programs into standalone binaries. - Source: Hacker News / about 1 month ago
For Python, you could make a proper deployment binary using Nuitka (in standalone mode – avoid onefile mode for this). I'm not pretending it's as easy as building a Go executable: you may have to do some manual hacking for more unusual unusual packages, and I don't think you can cross compile. I think a key element you're getting at is that Go executables have very few dependencies on OS packages, but with Python... - Source: Hacker News / about 2 months ago
There is already an AOT compiler for Python: Nuitka[0]. But I don't think it's much faster. And then there is mypyc[1] which uses mypy's static type annotations but is only slightly faster. And various other compilers like Numba and Cython that work with specialized dialects of Python to achieve better results, but then it's not quite Python anymore. [0] https://nuitka.net/ [1] - Source: Hacker News / 4 months ago
Nuitka deals pretty well with those in general: https://nuitka.net/. - Source: Hacker News / 10 months ago
Have a look at Nuitka, which is a "real" Python compiler into C. It uses CPython in its backend and should be completely compatible to "regular" Python. The compiled code can, but does not have to improve performance. It's probably worth looking into. Source: about 1 year ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
PyInstaller - PyInstaller is a program that freezes (packages) Python programs into stand-alone executables...
OpenCV - OpenCV is the world's biggest computer vision library
Cython - Cython is a language that makes writing C extensions for the Python language as easy as Python...
NumPy - NumPy is the fundamental package for scientific computing with Python
cx_Freeze - cx_Freeze is a set of scripts and modules for freezing Python scripts into executables in much the...