Update readme

README.md

@@ -1,6 +1,9 @@
 # Tunny
 
+[![License](https://img.shields.io/github/license/hrntsm/Tunny)](https://github.com/hrntsm/Tunny/blob/master/LICENSE)
+
 **Tunny** is Grasshopper's optimization component using Optuna, an open source hyperparameter auto-optimization framework.
+
 The following is taken from the official website
 
 >Optuna™, an open-source automatic hyperparameter optimization framework, automates the trial-and-error process of optimizing the hyperparameters. It automatically finds optimal hyperparameter values based on an optimization target. Optuna is framework agnostic and can be used with most Python frameworks, including Chainer, Scikit-learn, Pytorch, etc.
@@ -9,3 +12,19 @@ The following is taken from the official website
 
 Optuna official site
 - https://optuna.org/
+
+## Contact information
+
+[![Twitter](https://img.shields.io/twitter/follow/hiron_rgkr?style=social)](https://twitter.com/hiron_rgkr)
+
+- HP : [https://hiron.dev/](https://hiron.dev/)
+- Mail : support(at)hrntsm.com
+  - change (at) to @
+
+## License 
+
+Tunny is licensed under the [MIT](https://github.com/hrntsm/Tunny/blob/main/LICENSE) license.  
+Copyright© 2019-2021, hrntsm
+
+Release package is embedded Python runtime & optuna libraries.
+These depend on their own licenses.