Autoformer
telemanom
Autoformer | telemanom | |
---|---|---|
1 | 14 | |
1,732 | 950 | |
4.2% | - | |
5.4 | 0.0 | |
4 months ago | over 1 year ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | GNU General Public License v3.0 or later |
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.
Autoformer
-
[P] ts-tok: Time-Series Forecasting with Classification
The CustomDataset can use the datasets from here: google drive. source: https://github.com/thuml/Autoformer
telemanom
What are some alternatives?
Deep_XF - Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.
LSTM-Human-Activity-Recognition - Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
dtan - Official PyTorch implementation for our NeurIPS 2019 paper, Diffeomorphic Temporal Alignment Nets. TensorFlow\Keras version is available at tf_legacy branch.
stock-prediction-deep-neural-learning - Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting
TSAI-DeepNLP-END2.0
TensorFlow2.0_Notebooks - Implementation of a series of Neural Network architectures in TensorFow 2.0
CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.
tsai - Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
Twitter-sentiment-analysis - A sentiment analysis model trained with Kaggle GPU on 1.6M examples, used to make inferences on 220k tweets about Messi and draw insights from their results.