Skip to main content

A secure package for training machine learning models

Project description

OutdatedLabs - Secure Machine Learning Training Package

A secure and easy-to-use package for training machine learning models with remote server support.

Installation

pip install outdatedLabs

Quick Start

Use the package in your code:

from outdatedLabs import SecureModel

# Create a linear regression model
model = SecureModel.linearRegression()

# Train the model
model.train(
    dataset_hash="your_dataset_hash",
    features=["feature1", "feature2"],
    target="target_column"
)

# Get training metrics
metrics = model.get_metrics()
print(metrics)

# Download and load the trained model
model.download_model()
loaded_model = model.load_model()

Features

  • Secure model training with remote server support
  • Automatic dataset download and cleanup
  • Progress tracking with tqdm
  • Comprehensive error handling
  • Detailed logging
  • Support for multiple algorithms (currently Linear Regression)

Configuration

The package connects to a local ML training server by default at http://localhost:3000. You can change the server URL when creating a model:

model = SecureModel.linearRegression(server_url="http://your-server:3000")

API Reference

SecureModel

The main class for model training and management.

Methods

  • linearRegression(server_url: str = "http://localhost:3000"): Create a Linear Regression model
  • train(dataset_hash: str, features: List[str], target: str): Train the model
  • get_metrics() -> Dict: Get training metrics
  • download_model() -> str: Download the trained model
  • load_model() -> Any: Load the trained model

License

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

outdatedlabs-0.1.2.tar.gz (5.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

outdatedlabs-0.1.2-py3-none-any.whl (4.7 kB view details)

Uploaded Python 3

File details

Details for the file outdatedlabs-0.1.2.tar.gz.

File metadata

  • Download URL: outdatedlabs-0.1.2.tar.gz
  • Upload date:
  • Size: 5.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.2

File hashes

Hashes for outdatedlabs-0.1.2.tar.gz
Algorithm Hash digest
SHA256 2827fefb6eea751f345850e160250cc576b2389636990ac88f75dcfff5fecbeb
MD5 9f4442c28c8b2de6c71e6e6b05750a40
BLAKE2b-256 3e8dbf0d726d96784781723e715ed147fc4137b411ac0c5d1cc5045d5e664487

See more details on using hashes here.

File details

Details for the file outdatedlabs-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: outdatedlabs-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 4.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.2

File hashes

Hashes for outdatedlabs-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 c744d7e1d6ef5ffea2878e471032b5b47fdb493feb234313275e28d045e80a94
MD5 2d85c3ecc24bd394369aa9783fc044ae
BLAKE2b-256 92a0e935d6c8c3ec78db8fc58e9e26a3266a4529348822e4e9f1ad5a7bbba42c

See more details on using hashes here.

Supported by

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