Metadata-Version: 2.1
Name: veox
Version: 0.1.2
Summary: A client for the remote machine learning service with sklearn-like API
Home-page: https://github.com/yourusername/veox-client
Author: Jepson Taylor
Author-email: jep@google.me
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: requests>=2.25.1
Requires-Dist: python-socketio>=5.3.0
Requires-Dist: numpy>=1.19.5
Requires-Dist: joblib>=1.0.1

Veox Client
Veox Client is a Python package that provides a client for interacting with the Veox remote machine learning service. It offers an sklearn-like API for easy integration into your existing machine learning workflows.
Installation
You can install Veox Client using pip:
Copypip install veox
Usage
Here's a basic example of how to use Veox Client:
pythonCopyimport veox as v
import numpy as np
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split

# Generate a sample dataset
X, y = make_classification(n_samples=1000, n_features=20, n_classes=2, random_state=42)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# Initialize the remote model
model = v.init(key="YOUR_API_KEY", server_url="http://your-server-url:5000")

# Train the model
model.fit(X_train, y_train)

# Make predictions
y_pred = model.predict(X_test)

# Get prediction probabilities
y_prob = model.predict_proba(X_test)

# Calculate accuracy
accuracy = np.mean(y_pred == y_test)
print(f"Accuracy: {accuracy:.4f}")
Note
This package requires access to a running Veox server. Contact your system administrator or the Veox team for server access and API keys.
License
This project is licensed under the MIT License - see the LICENSE file for details.
