A lightweight, high-performance artificial intelligence toolkit designed to streamline predictive analytics and automated decision-making.
- Predictive Modeling: Built-in algorithms for classification, regression, and time-series forecasting.
- Automated Feature Engineering: Automatically detects, scales, and transforms raw data into optimal model inputs.
- Low-Latency Inference: Optimized for production environments requiring rapid, real-time API responses.
- Plug-and-Play Integration: Simple syntax that integrates seamlessly with existing Python data science pipelines.
Install the package via pip:
pip install vantage-ai
Train a model and generate predictions in just a few lines of code:
import vantage_ai as vai
# Load your dataset
data = vai.load_dataset("sales_data.csv")
# Initialize and train the model
model = vai.VantageModel(target="revenue")
model.fit(data)
# Make predictions on new data
predictions = model.predict(new_data)
print(predictions)This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules.
Currently, two official plugins are available:
- @vitejs/plugin-react uses Oxc
- @vitejs/plugin-react-swc uses SWC
The React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see this documentation.
If you are developing a production application, we recommend using TypeScript with type-aware lint rules enabled. Check out the TS template for information on how to integrate TypeScript and typescript-eslint in your project.