Skip to main content

Machine Learning and Forecasting tools

Project description

CircleCI codecov PyPI version

timeserio

timeserio is the missing link between pandas, scikit-learn and keras. It simplifies building end-to-end deep learning models - from a DataFrame through feature pipelines to multi-stage models with shared layers. While initially developed for tackling time series problems, it has since been used as a versatile tool for rapid ML model development and deployment.

Loosing track of big networks with multiple inputs and outputs? Forgetting to freeze the right layers? Struggling to re-generate the input features? timeserio can help!

complex_network

Documentation and Tutorials

Please see the official documentation on how to get started.

Features

  • Enable encapsulated, maintainable and reusable deep learning models
  • Feed data from pandas through scikit-learn feature pipelines to multiple neural network inputs
  • Manage complex architectures, layer sharing, partial freezing and re-training
  • Provide collection of extensible building blocks with emphasis on time series problems

Installation

pip install timeserio, or install from source - pip install -e .

See Getting Started

Development

We welcome contributions and enhancements to any part of the code base, documentation, or tool chain.

See CONTRIBUTING.md for details on setting up the development environment, running tests, etc.

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

timeserio-0.10.4.tar.gz (28.8 kB view hashes)

Uploaded Source

Built Distribution

timeserio-0.10.4-py2.py3-none-any.whl (41.6 kB view hashes)

Uploaded Python 2 Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page