AI-Aquatica 0.1.0

The project is used to analyze water quality data using AI/ML tools.

AI-Aquatica

AI-Aquatica is a comprehensive Python library designed to analyze water quality data using advanced AI/ML tools. This library facilitates the processing, analysis, and visualization of water quality indicators, helping researchers and professionals make informed decisions based on their data.

Features

• Data Import: Seamlessly import water quality data from various formats including CSV, Excel, JSON, SQL, and NoSQL databases.
• Data Cleaning: Efficiently clean your dataset by removing duplicates and handling missing values using various strategies.
• Data Standardization: Normalize and standardize your data for consistent analysis, including log, square root, and Box-Cox transformations.
• Handling Missing Data: Impute missing values using statistical methods or advanced AI/ML techniques like KNN, regression, and autoencoders.
• Ion Balance Calculations: Perform ion balance calculations to verify data integrity and identify potential errors.
• Statistical Analysis: Conduct basic and advanced statistical analyses, including correlation, ANOVA, and time series decomposition.
• AI/ML Analysis: Utilize machine learning models for regression, classification, clustering, anomaly detection, and data generation.
• Data Visualization: Create informative visualizations such as line plots, bar charts, scatter plots, heatmaps, PCA, t-SNE, and interactive bubble charts.
• Report Generation: Automatically generate comprehensive reports with statistical summaries and AI/ML analysis results.

Installation

Prerequisites

• Python 3.8 or higher
• pip (Python package installer)

Contributing

Contributions are welcome! Please see the contributing guidelines for more details.

License

This project is licensed under the MIT License.

Acknowledgments

Special thanks to all contributors and the open-source community for their support and contributions.