All Projects → jump-dev → Jumptutorials.jl

jump-dev / Jumptutorials.jl

Licence: mit
Tutorials on using JuMP for mathematical optimization in Julia

Programming Languages

julia
2034 projects

Projects that are alternatives of or similar to Jumptutorials.jl

Rnn Robinhood
Automated trading on Robinhood via RNN
Stars: ✭ 102 (-0.97%)
Mutual labels:  jupyter-notebook
Tsa
The Thalesians' Time Series Analysis (TSA) library
Stars: ✭ 102 (-0.97%)
Mutual labels:  jupyter-notebook
Deep ctr
Stars: ✭ 102 (-0.97%)
Mutual labels:  jupyter-notebook
Hic Data Analysis Bootcamp
Workshop on measuring, analyzing, and visualizing the 3D genome with Hi-C data.
Stars: ✭ 102 (-0.97%)
Mutual labels:  jupyter-notebook
Dlschl
Stars: ✭ 103 (+0%)
Mutual labels:  jupyter-notebook
Loads clustering
Data Science project to cluster loads coming from http://en.openei.org/datasets/files/961/pub/
Stars: ✭ 102 (-0.97%)
Mutual labels:  jupyter-notebook
Hackermath
Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way
Stars: ✭ 1,380 (+1239.81%)
Mutual labels:  jupyter-notebook
Ddn
Deep Declarative Networks
Stars: ✭ 103 (+0%)
Mutual labels:  jupyter-notebook
Scipy2017 Jupyter Widgets Tutorial
Notebooks for the SciPy 2017 tutorial "The Jupyter Interactive Widget Ecosystem"
Stars: ✭ 102 (-0.97%)
Mutual labels:  jupyter-notebook
End To End Time Series
This repository hosts code for my Time Series videos part of playlist here - https://www.youtube.com/playlist?list=PL3N9eeOlCrP5cK0QRQxeJd6GrQvhAtpBK
Stars: ✭ 103 (+0%)
Mutual labels:  jupyter-notebook
Dataminingnotesandpractice
记录我学习数据挖掘过程的笔记和见到的奇技,持续更新~
Stars: ✭ 103 (+0%)
Mutual labels:  jupyter-notebook
Models
DLTK Model Zoo
Stars: ✭ 101 (-1.94%)
Mutual labels:  jupyter-notebook
Pokelyzer
A webhook listener and database schema for doing geospatial analysis and advanced analytics on Pokemon Go data.
Stars: ✭ 102 (-0.97%)
Mutual labels:  jupyter-notebook
Storytelling With Data
Plots from the book "Storytelling with data" implementation using Python and matplotlib
Stars: ✭ 100 (-2.91%)
Mutual labels:  jupyter-notebook
Facemesh.pytorch
This is the PyTorch implementation of paper Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs (https://arxiv.org/pdf/1907.06724.pdf)
Stars: ✭ 101 (-1.94%)
Mutual labels:  jupyter-notebook
Keras Oneclassanomalydetection
[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.
Stars: ✭ 102 (-0.97%)
Mutual labels:  jupyter-notebook
Sst
SST: Single-Stream Temporal Action Proposals (Official Repo)
Stars: ✭ 102 (-0.97%)
Mutual labels:  jupyter-notebook
Advanced Deep Learning With Python
Advanced Deep Learning with Python
Stars: ✭ 103 (+0%)
Mutual labels:  jupyter-notebook
Python Data Science Handbook
A Chinese translation of Jake Vanderplas' "Python Data Science Handbook". 《Python数据科学手册》在线Jupyter notebook中文翻译
Stars: ✭ 102 (-0.97%)
Mutual labels:  jupyter-notebook
Advanced Machine Learning With Python
Code repository for Advanced Machine Learning with Python, published by Packt
Stars: ✭ 102 (-0.97%)
Mutual labels:  jupyter-notebook

JuMPTutorials.jl

Powered by NumFOCUS Build Status

This repository contains tutorials on JuMP, a domain-specific modeling language for mathematical optimization embedded in Julia. Tutorials can be viewed in the form of webpages, and interactive Jupyter notebooks. This set of tutorials is made to complement the documentation by providing practical examples of the concepts. For more details, please consult the JuMP documentation.

These tutorials are currently under development as a part of a Google Summer of Code project. The current list of tutorials that are planned can be viewed at the following issue. If there is a tutorial you would like to request, please add a comment to the above issue. Any other suggestions are welcome as well.

There are also some older notebooks available at juliaopt-notebooks repository. Most of these were built using prior versions of JuMP and may not function correctly, but they can assist in implementing some concepts. There are also some code examples available in the main JuMP repo.

Run Notebooks in the Browser

Binder

To try out any of the tutorials in the browser without downloading Julia, click on the launch binder button above. Note that this functionality only supports open-source solvers which do not have additional requirements (for e.g. BLAS or MATLAB). This is also very slow and can take several minutes to start as it has to first install Julia and all the dependencies. Thus, you should download and run the notebooks on your PC for the best experience.

Table of Contents

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].