Update README

Author: YoanSallami

README.md

@@ -41,17 +41,6 @@ Too busy to read the documentation? Give the [llms.txt](https://synalinks.github
 
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-## Want to learn how to build neuro-symbolic systems?
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-We provide a suite of notebooks available in [Google Colab](https://colab.research.google.com/) so you can learn about the future of AI and become a neuro-symbolic expert!
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-We specifically designed them to be easy to start and become more complex as you learn more, so we encourage you explore them in the provided order.
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-1. [Working With Data Models](examples/1_working_with_data_models.ipynb)[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1eJoFNn6wAFVd2vqrmgIHEwgzHfbp0Lkb?usp=sharing)
-2. [Working With Programs](examples/2_working_with_programs.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1RRZUIGW6r61Rs38EQl52beRVZyIoYXe_?usp=sharing)
-3. [Parrallel and Conditional Branches]()
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 ## What is Synalinks?
 
 Synalinks is an open-source framework that makes it easy to create, evaluate, train, and deploy industry-standard Language Models (LMs) applications like **graph RAGs, autonomous agents, multi-agent systems or self-evolving systems**. Synalinks follows the principle of *progressive disclosure of complexity*: meaning that simple workflows should be quick and easy, while arbitrarily advanced ones should be possible via a clear path that builds upon what you've already learned.