Update README.md

README.md

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 This project focuses on text Classification that works on identifying different authors writing styles in Gutenberg digital books and predict to which author or genre the piece of writing belongs. <br>
 
+![image](images/words.png)
+
 Prepare and Preprocess the data which include Clean Data, Feature Extraction, and Transform the data to Bag of Words (BOW) and TF-IDF Vectorizer with and without N-Grams.
 
 for the classification Decision Tree Model, SVM Model, KNN Model were tested.
-The SVM model gave the best accuracy with the "linear" kernel we obtained an accuracy of 98.7%, the linear kernel provides faster performance.
+The SVM model gave the best accuracy with the "linear" kernel we obtained an accuracy of 98.7%, the linear kernel provides faster performance. <br>
+
+Collected all the accuracy we obtained from each model:
+
+![image](images/models.png)