Welcome to the Evidently-AI repository! This repository focuses on using Evidently AI, a tool for monitoring and evaluating machine learning models. Whether you're new to Evidently AI or looking to enhance your model evaluation skills, you'll find tutorials, examples, and projects here to support your learning journey.
- Introduction
- Topics Covered
- Getting Started
- Contributing
- Challenges Faced
- Lessons Learned
- Why I Created This Repository
- License
- Contact
This repository provides comprehensive resources for learning and using Evidently AI, covering fundamental concepts, practical examples, and hands-on projects. Whether you're evaluating model performance, monitoring drift, or exploring Evidently AI's capabilities, this repository will guide you through the basics and advanced uses of Evidently AI.
- Setting Up Evidently AI: Installation and basic project configuration.
- Model Evaluation: Tools and techniques for assessing model performance.
- Monitoring Drift: Methods for detecting and managing model drift.
- Visualization: Creating visualizations to interpret model results.
- Integration: Connecting Evidently AI with various machine learning frameworks.
- Examples and Projects: Real-world applications and demo projects.
To get started with Evidently-AI projects, follow these steps:
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Clone the repository:
git clone https://github.com/Md-Emon-Hasan/Evidently-AI.git
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Navigate to the project directory:
cd Evidently-AI
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Explore topics and examples:
- Each directory contains tutorials, examples, or projects related to specific Evidently AI topics.
Contributions to improve or expand the repository are welcome! Here's how you can contribute:
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Fork the repository.
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Create a new branch:
git checkout -b feature/new-feature
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Make your changes:
- Add new tutorials, examples, or improve existing documentation.
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Commit your changes:
git commit -am 'Add a new feature or update'
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Push to the branch:
git push origin feature/new-feature
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Submit a pull request.
Throughout the development of this repository, challenges were encountered, including:
- Understanding Evidently AI's API and customization options.
- Integrating Evidently AI with different machine learning workflows.
- Managing model performance metrics and visualizations effectively.
Key lessons learned from developing this repository include:
- Mastery of Evidently AI fundamentals and best practices.
- Practical application of Evidently AI in monitoring and evaluating machine learning models.
- Importance of clear documentation and structured project organization in model evaluation.
I created this repository to provide a structured and beginner-friendly resource for learning Evidently AI. It aims to empower developers and data scientists with the tools and knowledge to effectively monitor and evaluate their machine learning models using Evidently AI.
This project is licensed under the GNU General Public License v3.0. See the LICENSE file for more details.
- Email: [email protected]
- WhatsApp: +8801834363533
- GitHub: Md-Emon-Hasan
- LinkedIn: Md Emon Hasan
- Facebook: Md Emon Hasan
Feel free to reach out for any questions, feedback, or collaboration opportunities!
Feel free to customize this template further to better reflect the specifics of your Evidently-AI repository.