Automated Time-Series Forecasting
Project description
AutoTSF
Automated time-series forecast pipeline with state-of-art machine learning and deep learning algorithm. 🚀🚀🚀
Installation
Use the package manager pip to install AutoTSF.
$ pip install autotsf
Getting Started
from autotsf import AutoTSF # Import
auto_tsf = AutoTSF() # Initialization
auto_tsf.train(data) # automated feature engineering and model training
pred_df = auto_tsf.predict(num_steps=7) # one week forecast
Authors
See also the list of contributors who participated in this project.
License
This project is licensed under the MIT License - see the LICENSE file for details
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Autotsf-0.0.8.tar.gz
(12.8 kB
view details)
Built Distribution
Autotsf-0.0.8-py3-none-any.whl
(20.9 kB
view details)
File details
Details for the file Autotsf-0.0.8.tar.gz
.
File metadata
- Download URL: Autotsf-0.0.8.tar.gz
- Upload date:
- Size: 12.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.2
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | cb858e634f6a6ac5e37d7b6d44bc3d6b998b291fe53aa692b6dde1eff5bbb3ea |
|
MD5 | 76d9fb1e361a74dd354b8399f6a22fae |
|
BLAKE2b-256 | 0e11f5d093c2daf23ea48c84739d70de42ea601abeb94fcfe7e375d7b24395b5 |
File details
Details for the file Autotsf-0.0.8-py3-none-any.whl
.
File metadata
- Download URL: Autotsf-0.0.8-py3-none-any.whl
- Upload date:
- Size: 20.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.2
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 745ee34aeaf5fb5bc5433061d5d9c29bfffd24813c6f9e1b7277751b3c3bca28 |
|
MD5 | 0a424cbad6c626653e4ca7dae4ee49ea |
|
BLAKE2b-256 | 015b7d5dddffee4464e379af4f9e3d0ca178add3d40041599b2feee851adc38d |