few small changes to README.md

README.md

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 </h1>
 
-<h3 align="center">Hyperparameter Optimization for TensorFlow and Keras</h3>
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-<p align="center">
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-  <a href="https://travis-ci.org/autonomio/talos">
-    <img src="https://img.shields.io/travis/autonomio/talos/master.svg?style=for-the-badge&logo=appveyor" alt="Talos Travis">
-  </a>
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-  <a href="https://coveralls.io/github/autonomio/talos">
-    <img src="https://img.shields.io/coveralls/github/autonomio/talos.svg?style=for-the-badge&logo=appveyor" alt="Talos Coveralls">
-  </a>
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-</p>
+<h3 align="center">Bullet-Proof Hyperparameter Experiments for TensorFlow and Keras</h3>
 
 <p align="center">
   <a href="#talos">Talos</a> •
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 Talos is made for researchers, data scientists, and data engineers that want to remain in **complete control of their TensorFlow (tf.keras) and Keras models**, but are tired of mindless parameter hopping and confusing optimization solutions that add complexity instead of reducing it. 
 
-**Within minutes, without learning any new syntax,** Talos allows you to configure, perform, and evaluate hyperparameter experiments that yield state-of-the-art results across a wide range of prediction tasks. Talos provides the **simplest and yet most powerful** available method for hyperparameter optimization with TensorFlow (tf.keras) and Keras.
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 <hr>
 
 ### :wrench: Key Features
 
-Based on what no doubt constitutes a "biased" review (being our own) of more than ~30 hyperparameter tuning and optimization solutions, Talos comes on top in terms of intuitive, easy-to-learn, highly permissive access to critical hyperparameter experimentation capabilities. Key features include:
+**Within minutes, without learning any new syntax,** Talos allows you to configure, perform, and evaluate hyperparameter experiments that yield state-of-the-art results across a wide range of prediction tasks. Talos provides the **simplest and yet most powerful** available method for hyperparameter optimization with TensorFlow (tf.keras) and Keras. Key features include:
 
   - Single-line optimize-to-predict pipeline `talos.Scan(x, y, model, params).predict(x_test, y_test)`
   - Automated hyperparameter optimization