Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack
mltrace tutorial Date: October 2021 This tutorial builds a training and testing pipeline for a toy ML prediction problem: to predict whether a passeng
Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera
Fully Adversarial Mosaics (FAMOS) Pytorch implementation of the paper "Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Imag
dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu
About Solve CTF offline disconnection problem - based on python3's small crawler, support keyword search and local map bed establishment, currently support Jianshu, xianzhi,anquanke,freebuf,seebug
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L
pure-predict speeds up and slims down machine learning prediction applications. It is a foundational tool for serverless inference or small batch prediction with popular machine learning frameworks l
MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th
ORCCA Optimal Randomized Canonical Correlation Analysis This project is for the python version of ORCCA algorithm. It depends on Numpy for matrix calc
Repository Status for Scikit-learn Live webpage Auto updating website that tracks closed & open issues/PRs on scikit-learn/scikit-learn. Running local
MLOps Zoomcamp Our MLOps Zoomcamp course Sign up here: https://airtable.com/shrCb8y6eTbPKwSTL (it's not automated, you will not receive an email immed
LRM-Squannacook Input data for generating stochastic streamflows are observed and simulated timeseries of streamflow. their format needs to be CSV wit
Using PySpark we can process data from Hadoop HDFS, AWS S3, and many file systems. PySpark also is used to process real-time data using Streaming and
This is a Cricket Score Predictor that predicts the first innings score of a T20 Cricket match using Machine Learning. It is a Web Application.
Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern
Py-boost: a research tool for exploring GBDTs Modern gradient boosting toolkits are very complex and are written in low-level programming languages. A
Machine Learning from Scratch Author: Shengxuan Wang From: Oregon State University Content: Building Machine Learning model from Scratch, without usin
A data preprocessing package for time series data. Design for machine learning and deep learning.
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