All Projects → Mcompetitions → M5 Methods

Mcompetitions / M5 Methods

Data, Benchmarks, and methods submitted to the M5 forecasting competition

Projects that are alternatives of or similar to M5 Methods

Spell Checker
A seq2seq model that can correct spelling mistakes.
Stars: ✭ 193 (+0.52%)
Mutual labels:  jupyter-notebook
Coursera Deep Learning Specialization
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
Stars: ✭ 188 (-2.08%)
Mutual labels:  jupyter-notebook
Snippet
just some code snippet
Stars: ✭ 194 (+1.04%)
Mutual labels:  jupyter-notebook
One Hundred Layers Tiramisu
Keras Implementation of The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation by (Simon Jégou, Michal Drozdzal, David Vazquez, Adriana Romero, Yoshua Bengio)
Stars: ✭ 193 (+0.52%)
Mutual labels:  jupyter-notebook
Machinelearningnotebooks
Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
Stars: ✭ 2,790 (+1353.13%)
Mutual labels:  jupyter-notebook
Intro To Dsp With Python
Stars: ✭ 194 (+1.04%)
Mutual labels:  jupyter-notebook
Extendedtinyfaces
Detecting and counting small objects - Analysis, review and application to counting
Stars: ✭ 193 (+0.52%)
Mutual labels:  jupyter-notebook
Compstats
Code for a workshop on statistical interference using computational methods in Python.
Stars: ✭ 194 (+1.04%)
Mutual labels:  jupyter-notebook
Mobile Yolov5 Pruning Distillation
mobilev2-yolov5s剪枝、蒸馏,支持ncnn,tensorRT部署。ultra-light but better performence!
Stars: ✭ 192 (+0%)
Mutual labels:  jupyter-notebook
Ctr nn
基于深度学习的CTR预估,从FM推演各深度学习CTR预估模型(附代码)
Stars: ✭ 194 (+1.04%)
Mutual labels:  jupyter-notebook
Scribe
Realistic Handwriting with Tensorflow
Stars: ✭ 193 (+0.52%)
Mutual labels:  jupyter-notebook
Tensorflow
Project containig related material for my TensorFlow articles
Stars: ✭ 2,371 (+1134.9%)
Mutual labels:  jupyter-notebook
Quantecon Notebooks Python
A Repository of Notebooks for the Python Lecture Site
Stars: ✭ 194 (+1.04%)
Mutual labels:  jupyter-notebook
Nn compression
Stars: ✭ 193 (+0.52%)
Mutual labels:  jupyter-notebook
Jupyterhub Deploy Teaching
Reference deployment of JupyterHub and nbgrader on a single server
Stars: ✭ 194 (+1.04%)
Mutual labels:  jupyter-notebook
Deep learning tutorial
[ko] 패스트캠퍼스 강의 자료
Stars: ✭ 193 (+0.52%)
Mutual labels:  jupyter-notebook
Open Visualizations
Visualizations based on best open science practices.
Stars: ✭ 194 (+1.04%)
Mutual labels:  jupyter-notebook
Nbqa
Run any standard Python code quality tool on a Jupyter Notebook
Stars: ✭ 193 (+0.52%)
Mutual labels:  jupyter-notebook
Sklearn Benchmarks
A centralized repository to report scikit-learn model performance across a variety of parameter settings and data sets.
Stars: ✭ 194 (+1.04%)
Mutual labels:  jupyter-notebook
Kite Python Blog Post Code
Code snippets from Kite blog posts
Stars: ✭ 194 (+1.04%)
Mutual labels:  jupyter-notebook

M5-methods

Benchmarks and winning methods of the M5 forecasting competition

"validation": Code used for producing the forecasts of the benchmarks (both of "Accuracy" and "Uncertainty" competitions).

"Scores and Ranks.xlsx": Scores and ranks of the top 50 submissions of the M5 "Accuracy" and M5 "Uncertainty" competitions. The scores of the benchmarks are also provided.

"M5-Competitors-Guide.pdf": Provides information about the set-up of the competition, the data set, the evaluation measures, the prizes, the submission files, and the benchmarks.

The following link includes the abovomentioned items PLUS:

"Dataset": The data set of the competition, i.e., unit sales (train and test set) and information about calendar, promotions, and prices. The data set is also available for R users in a .Rdata format.

"Accuracy Submissions": The forecasts of the 24 benchmarks of the M5 "Accuracy" competition and the submissions made by the top 50 performing methods.

"Uncertainty Submissions": The forecasts of the 6 benchmarks of the M5 "Uncertainty" competition and the submissions made by the top 50 performing methods.

https://drive.google.com/drive/folders/1D6EWdVSaOtrP1LEFh1REjI3vej6iUS_4?usp=sharing

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].