tsfresh
Time-Series-Transformer
tsfresh | Time-Series-Transformer | |
---|---|---|
4 | 18 | |
8,096 | 191 | |
0.5% | - | |
5.4 | 0.0 | |
15 days ago | over 3 years ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
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.
tsfresh
-
For deep learning practitioners in industry, is the workflow always this annoying? [D]
This is definitely a good thing to try for time-series; you can automate your feature extraction too (eg using https://github.com/blue-yonder/tsfresh ).
-
[D] Incorporating external data in LSTM models for sales forecasting in e-commerce
don't forget your feature engineering -> https://github.com/blue-yonder/tsfresh
-
[R] Approach to identify clusters on a time series
Rather than the exact clustering algorithm, I think the main issue here is the feature extraction for the clustering. https://github.com/blue-yonder/tsfresh might be useful for that.
- Automatic time series feature extraction based on scalable hypothesis tests
Time-Series-Transformer
What are some alternatives?
tsflex - Flexible time series feature extraction & processing
nixtlats - Deep Learning for Time Series Forecasting.
TimeSynth - A Multipurpose Library for Synthetic Time Series Generation in Python
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Deep_Learning_Machine_Learning_Stock - Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
pycaret - An open-source, low-code machine learning library in Python
SDV - Synthetic data generation for tabular data
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
darts - A python library for user-friendly forecasting and anomaly detection on time series.
stock-prediction-deep-neural-learning - Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting
tsfel - An intuitive library to extract features from time series.
Anomaly_Detection_Tuto - Anomaly detection tutorial on univariate time series with an auto-encoder