DeepADoTS VS pytorch-forecasting

Compare DeepADoTS vs pytorch-forecasting and see what are their differences.

Our great sponsors
  • Scout APM - Less time debugging, more time building
  • SonarQube - Static code analysis for 29 languages.
  • OPS - Build and Run Open Source Unikernels
DeepADoTS pytorch-forecasting
1 2
416 1,639
3.4% -
0.0 9.4
5 months ago 7 days ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

DeepADoTS

Posts with mentions or reviews of DeepADoTS. We have used some of these posts to build our list of alternatives and similar projects.

pytorch-forecasting

Posts with mentions or reviews of pytorch-forecasting. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-12.

What are some alternatives?

When comparing DeepADoTS and pytorch-forecasting you can also consider the following projects:

darts - A python library for easy manipulation and forecasting of time series.

Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

pytorch-lightning - The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

tslearn - A machine learning toolkit dedicated to time-series data

Lime-For-Time - Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification

uncertainty-baselines - High-quality implementations of standard and SOTA methods on a variety of tasks.

lightning-transformers - Flexible interface for high-performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra.

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.

snntorch - Deep and online learning with spiking neural networks in Python

Informer2020 - The GitHub repository for the paper "Informer" accepted by AAAI 2021.

Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time