Library for time-series-forecasting-as-a-service.

Overview

TIMEX

Tests with PyTest Coverage PyPI PyPI - Downloads

TIMEX (referred in code as timexseries) is a framework for time-series-forecasting-as-a-service.

Its main goal is to provide a simple and generic tool to build websites and, more in general, platforms, able to provide the forecasting of time-series in the "as-a-service" manner.

This means that users should interact with the service as less as possible.

An example of the capabilities of TIMEX can be found at covid-timex.it
That website is built using the Dash, on which the visualization part of TIMEX is built. A deep explanation is available in the dedicated repository.

Installation

The main two dependencies of TIMEX are Facebook Prophet and PyTorch. If you prefer, you can install them beforehand, maybe because you want to choose the CUDA/CPU version of Torch.

However, installation is as simple as running:

pip install timexseries

Get started

Please, refer to the Examples folder. You will find some Jupyter Notebook which illustrate the main characteristics of TIMEX. A Notebook explaining the covid-timex.it website is present, along with the source code of the site, here.

Documentation

The full documentation is available at here.

Contacts

If you have questions, suggestions or problems, feel free to open an Issue. You can contact us at:

Implementation of paper "Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal"

Patch-wise Adversarial Removal Implementation of paper "Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal

4 Oct 12, 2022
NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go

NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go This repository provides our implementation of the CVPR 2021 paper NeuroMorp

Meta Research 35 Dec 08, 2022
KSAI Lite is a deep learning inference framework of kingsoft, based on tensorflow lite

KSAI Lite is a deep learning inference framework of kingsoft, based on tensorflow lite

80 Dec 27, 2022
Planner_backend - Academic planner application designed for students and counselors.

Planner (backend) Academic planner application designed for students and advisors.

2 Dec 31, 2021
simple demo codes for Learning to Teach with Dynamic Loss Functions

Learning to Teach with Dynamic Loss Functions This repo contains the simple demo for the NeurIPS-18 paper: Learning to Teach with Dynamic Loss Functio

Lijun Wu 15 Dec 30, 2021
PyKaldi GOP-DNN on Epa-DB

PyKaldi GOP-DNN on Epa-DB This repository has the tools to run a PyKaldi GOP-DNN algorithm on Epa-DB, a database of non-native English speech by Spani

18 Dec 14, 2022
"Learning Free Gait Transition for Quadruped Robots vis Phase-Guided Controller"

PhaseGuidedControl The current version is developed based on the old version of RaiSim series, and possibly requires further modification. It will be

X-Mechanics 12 Oct 21, 2022
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

Build Type Linux MacOS Windows Build Status OpenPose has represented the first real-time multi-person system to jointly detect human body, hand, facia

25.7k Jan 09, 2023
Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)

NBFNet: Neural Bellman-Ford Networks This is the official codebase of the paper Neural Bellman-Ford Networks: A General Graph Neural Network Framework

MilaGraph 136 Dec 21, 2022
Can we do Customers Segmentation using PHP and Unsupervized Machine Learning ? Yes we can ! 🤡

Customers Segmentation using PHP and Rubix ML PHP Library Can we do Customers Segmentation using PHP and Unsupervized Machine Learning ? Yes we can !

Mickaël Andrieu 11 Oct 08, 2022
RuDOLPH: One Hyper-Modal Transformer can be creative as DALL-E and smart as CLIP

[Paper] [Хабр] [Model Card] [Colab] [Kaggle] RuDOLPH 🦌 🎄 ☃️ One Hyper-Modal Tr

Sber AI 230 Dec 31, 2022
Medical Image Segmentation using Squeeze-and-Expansion Transformers

Medical Image Segmentation using Squeeze-and-Expansion Transformers Introduction This repository contains the code of the IJCAI'2021 paper 'Medical Im

askerlee 172 Dec 20, 2022
EdMIPS: Rethinking Differentiable Search for Mixed-Precision Neural Networks

EdMIPS is an efficient algorithm to search the optimal mixed-precision neural network directly without proxy task on ImageNet given computation budgets. It can be applied to many popular network arch

Zhaowei Cai 47 Dec 30, 2022
Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP

Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP Abstract: We introduce a method that allows to automatically se

Daniil Pakhomov 134 Dec 19, 2022
An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge.

Bottom-Up and Top-Down Attention for Visual Question Answering An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge. The

Hengyuan Hu 731 Jan 03, 2023
PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Condition Layer Normalization and Semi-Supervised Training in Text-To-Speech

Cross-Speaker-Emotion-Transfer - PyTorch Implementation PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Conditio

Keon Lee 114 Jan 08, 2023
Build Graph Nets in Tensorflow

Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact DeepMind 5.2k Jan 05, 2023

Automatic deep learning for image classification.

AutoDL AutoDL automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few line

wenqi 2 Oct 12, 2022
TensorFlow implementation of the paper "Hierarchical Attention Networks for Document Classification"

Hierarchical Attention Networks for Document Classification This is an implementation of the paper Hierarchical Attention Networks for Document Classi

Quoc-Tuan Truong 83 Dec 05, 2022
[CVPR 2021] A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts

Visual-Reasoning-eXplanation [CVPR 2021 A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts] Project Page | Vid

Andy_Ge 54 Dec 21, 2022