Data science tools from Moz
Project description
A grab bag of assorted Data science tools from Moz.
Currently includes:
Utilities for training/evaluating machine learning models:
Cross validation
Evaluation metrics (AUC, F1, etc)
Training models in parallel
Ensemble model selection
PCA
A generic way to specify model inputs
Some linear models:
Linear Regression
Logistic Regression
GLM
Installing
pip install mozsci
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
mozsci-0.9.0.tar.gz
(34.2 kB
view details)
Built Distributions
File details
Details for the file mozsci-0.9.0.tar.gz
.
File metadata
- Download URL: mozsci-0.9.0.tar.gz
- Upload date:
- Size: 34.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 58ced785948bcff16ad5886f82c333d25bb684c1c7e1fc8172e312c030102924 |
|
MD5 | ac1b09e85c984807bfedda23b5e90026 |
|
BLAKE2b-256 | c38b32a45f9d8d1f832060f657e2e640ca8295a753bbdf3d3b57ce33db89be4d |
Provenance
File details
Details for the file mozsci-0.9.0-py2.7-macosx-10.10-intel.egg
.
File metadata
- Download URL: mozsci-0.9.0-py2.7-macosx-10.10-intel.egg
- Upload date:
- Size: 117.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 563c144ee86f9c5f3557a3f2795c15ba18e2fa0177c40896101d7877abe8a16b |
|
MD5 | 280224b5214d2e38d60d2d49faa66b13 |
|
BLAKE2b-256 | 8edea152197cc4478a2d10ad4616aa5b3cd02d325e953506d42b8dbba6c36fd0 |
Provenance
File details
Details for the file mozsci-0.9.0-cp27-none-macosx_10_10_intel.whl
.
File metadata
- Download URL: mozsci-0.9.0-cp27-none-macosx_10_10_intel.whl
- Upload date:
- Size: 80.3 kB
- Tags: CPython 2.7, macOS 10.10+ intel
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | ec10e4ab5cc6d6feba9153db2b2cc3805a98020d163c7deb6f7b975459b5a427 |
|
MD5 | 7ac3b77586b1891491a29d04e6d3e43d |
|
BLAKE2b-256 | 777ae0f3c739bda4f12803eab4eb309819f5acd67eeabc4e83fc34a0a43c9640 |