AlphaD3M: NYU's AutoML System
Project description
AlphaD3M is an AutoML system that automatically searches for models and derives end-to-end pipelines that read, pre-process the data, and train the model. AlphaD3M leverages recent advances in deep reinforcement learning and is able to adapt to different application domains and problems through incremental learning.
AlphaD3M provides data scientists and data engineers the flexibility to address complex problems by leveraging the Python ecosystem, including open-source libraries and tools, support for collaboration, and infrastructure that enables transparency and reproducibility.
This repository is part of New York University's implementation of the Data Driven Discovery project (D3M).
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
Built Distribution
File details
Details for the file alphad3m-containers-0.0.0.tar.gz
.
File metadata
- Download URL: alphad3m-containers-0.0.0.tar.gz
- Upload date:
- Size: 6.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.49.0 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9206bc28024434ad6188c2bf65979a4ce739754001888ea4dfc523b4fed3d32a |
|
MD5 | 8a0ba8c4ed9220ce0ad263f4799a6122 |
|
BLAKE2b-256 | aec3124fbabc81dfcfdecf97e156ddfae43d89f9e7755b8aa599bd55e350353a |
File details
Details for the file alphad3m_containers-0.0.0-py3-none-any.whl
.
File metadata
- Download URL: alphad3m_containers-0.0.0-py3-none-any.whl
- Upload date:
- Size: 7.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.49.0 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | cdca4d36bb6b403eea2ecb0ed16a2046f2fa9239a596d316beea02209cc2b102 |
|
MD5 | 1c73d1cdf98a3d80d26874129dbb0d6c |
|
BLAKE2b-256 | 81fbc33735abd81a6a264fb5292c5c02570f8fe11defce7e620ccf1e0a53e1dd |