Interactive Parallel Computing in Python

Overview

Interactive Parallel Computing with IPython

ipyparallel is the new home of IPython.parallel. ipyparallel is a Python package and collection of CLI scripts for controlling clusters for Jupyter.

ipyparallel contains the following CLI scripts:

  • ipcluster - start/stop a cluster
  • ipcontroller - start a scheduler
  • ipengine - start an engine

Install

Install ipyparallel:

pip install ipyparallel

To enable the IPython Clusters tab in Jupyter Notebook:

ipcluster nbextension enable

To disable it again:

ipcluster nbextension disable

See the documentation on configuring the notebook server to find your config or setup your initial jupyter_notebook_config.py.

JupyterHub Install

To install for all users on JupyterHub, as root:

jupyter nbextension install --sys-prefix --py ipyparallel
jupyter nbextension enable --sys-prefix --py ipyparallel
jupyter serverextension enable --sys-prefix --py ipyparallel

Run

Start a cluster:

ipcluster start

Use it from Python:

import os
import ipyparallel as ipp

rc = ipp.Client()
ar = rc[:].apply_async(os.getpid)
pid_map = ar.get_dict()

See the docs for more info.

Owner
IPython
interactive computing in Python
IPython
MLR - Machine Learning Research

Machine Learning Research 1. Project Topic 1.1. Exsiting research Benmark: https://paperswithcode.com/sota ACL anthology for NLP papers: http://www.ac

Charles 69 Oct 20, 2022
Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)

Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)

141 Dec 27, 2022
The project's goal is to show a real world application of image segmentation using k means algorithm

The project's goal is to show a real world application of image segmentation using k means algorithm

2 Jan 22, 2022
A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize

⚡ funk-svd funk-svd is a Python 3 library implementing a fast version of the famous SVD algorithm popularized by Simon Funk during the Neflix Prize co

Geoffrey Bolmier 171 Dec 19, 2022
PyPOTS - A Python Toolbox for Data Mining on Partially-Observed Time Series

A python toolbox/library for data mining on partially-observed time series, supporting tasks of forecasting/imputation/classification/clustering on incomplete multivariate time series with missing va

Wenjie Du 179 Dec 31, 2022
GroundSeg Clustering Optimized Kdtree

ground seg and clustering based on kitti velodyne data, and a additional optimized kdtree for knn and radius nn search

2 Dec 02, 2021
Upgini : data search library for your machine learning pipelines

Automated data search library for your machine learning pipelines → find & deliver relevant external data & features to boost ML accuracy :chart_with_upwards_trend:

Upgini 175 Jan 08, 2023
Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application

Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application (with docker-compose).

Philip May 2 Dec 03, 2021
A library to generate synthetic time series data by easy-to-use factors and generator

timeseries-generator This repository consists of a python packages that generates synthetic time series dataset in a generic way (under /timeseries_ge

Nike Inc. 87 Dec 20, 2022
Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc)

Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed

Chris Yuan 1 Feb 06, 2022
a distributed deep learning platform

Apache SINGA Distributed deep learning system http://singa.apache.org Quick Start Installation Examples Issues JIRA tickets Code Analysis: Mailing Lis

The Apache Software Foundation 2.7k Jan 05, 2023
A collection of machine learning examples and tutorials.

machine_learning_examples A collection of machine learning examples and tutorials.

LazyProgrammer.me 7.1k Jan 01, 2023
Magenta: Music and Art Generation with Machine Intelligence

Magenta is a research project exploring the role of machine learning in the process of creating art and music. Primarily this involves developing new

Magenta 18.1k Dec 30, 2022
Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters

Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters. It also works with any regressor compatible with the scikit-learn API (pipelines, CatBoost, LightGBM

Joaquín Amat Rodrigo 297 Jan 09, 2023
AutoX是一个高效的自动化机器学习工具,它主要针对于表格类型的数据挖掘竞赛。 它的特点包括: 效果出色、简单易用、通用、自动化、灵活。

English | 简体中文 AutoX是什么? AutoX一个高效的自动化机器学习工具,它主要针对于表格类型的数据挖掘竞赛。 它的特点包括: 效果出色: AutoX在多个kaggle数据集上,效果显著优于其他解决方案(见效果对比)。 简单易用: AutoX的接口和sklearn类似,方便上手使用。

4Paradigm 431 Dec 28, 2022
A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

Oleksii Trekhleb 1.4k Jan 06, 2023
Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )

implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map,

Mohamadreza Rezaei 1 Jan 19, 2022
Used Logistic Regression, Random Forest, and XGBoost to predict the outcome of Search & Destroy games from the Call of Duty World League for the 2018 and 2019 seasons.

Call of Duty World League: Search & Destroy Outcome Predictions Growing up as an avid Call of Duty player, I was always curious about what factors led

Brett Vogelsang 2 Jan 18, 2022
Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice

Responsible AI Workshop Responsible innovation is top of mind. As such, the tech industry as well as a growing number of organizations of all kinds in

Microsoft 9 Sep 14, 2022
Crunchdao - Python API for the Crunchdao machine learning tournament

Python API for the Crunchdao machine learning tournament Interact with the Crunc

3 Jan 19, 2022