Skip to main content

A computation graph library for feature engineering with Numpy data

Project description

Megatron is a framework for building computation graphs for
feature engineering in machine learning, with Numpy arrays as the data type.
Use Megatron if you want to:
- Do feature engineering in a modular and functional way, building up features one step at a time
- Use disk space to save time by caching feature sets for easy reloading
- Train feature engineering modules on training data and apply them to testing data
- Write custom functions for complex transformations, but access built-in functions for quick and common transformations
- Build feature engineering like you build Keras models (the API is heavily inspired by Keras)
Or any combination of these.
Megatron is distributed under the MIT license.

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

Megatron-0.1.1.tar.gz (9.9 kB view details)

Uploaded Source

File details

Details for the file Megatron-0.1.1.tar.gz.

File metadata

  • Download URL: Megatron-0.1.1.tar.gz
  • Upload date:
  • Size: 9.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.2.0 requests-toolbelt/0.8.0 tqdm/4.25.0 CPython/3.7.0

File hashes

Hashes for Megatron-0.1.1.tar.gz
Algorithm Hash digest
SHA256 947d6da0172056927e6941e8b3844d0713b3bddafed13877e88f4632e738ff13
MD5 65de04805d008f4268aa0bb4a474d6b2
BLAKE2b-256 1b53e4ed54fcca1457d24b31179a8b3e191e3679a553c17bcd6eefd7def5bc37

See more details on using hashes here.

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