A low-code library for machine learning pipelines
Project description
blitzml
Automate machine learning piplines rapidly
How to install
python -m pip install blitzml
Usage
from blitzml.csv import Pipeline
dataset_folder = "auxiliary/data/" # contains train.csv and test.csv
ground_truth_path = "auxiliary/ground_truth.csv"
output_folder_path = "auxiliary/output/"
auto = Pipeline(dataset_folder, ground_truth_path, output_folder_path, classifier = 'RF', n_estimators = 50)
auto.preprocess()
auto.train_the_model()
auto.gen_metrics_dict()
metrics_dict = auto.metrics_dict
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
blitzml-0.1.0.tar.gz
(4.2 kB
view details)
Built Distribution
File details
Details for the file blitzml-0.1.0.tar.gz
.
File metadata
- Download URL: blitzml-0.1.0.tar.gz
- Upload date:
- Size: 4.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.4
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | a036d26b22ec3225a606db04fbefeccd8195bbc0daaa767258fb75eb614c4ceb |
|
MD5 | 45b814fce7b02525fd2e6d66bae99b61 |
|
BLAKE2b-256 | eb284b9f7b8b520337e703bb4cf8dab2367c49b716b8217871c133894b38dc9f |
File details
Details for the file blitzml-0.1.0-py3-none-any.whl
.
File metadata
- Download URL: blitzml-0.1.0-py3-none-any.whl
- Upload date:
- Size: 4.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.4
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 391cb32a5bcab9bed4b3fd7e8750092a371b6707374ccde0eee8c62125d2cf66 |
|
MD5 | cf63462964f979e9a4e58a3f5f0cd539 |
|
BLAKE2b-256 | e0628cacdc72f02b7d51203fc5df34a1dcfce7289195e87ed26ee40dfbde3d32 |