Update README.md

Author: ksator

README.md

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 Please visit the [wiki](https://github.com/ksator/Machine_Learning_with_Python/wiki)  
 
+- [What to find in this repository](https://github.com/ksator/Machine_Learning_with_Python/wiki/What-to-find-in-this-repository)
+- [About the Python libraries used in this repo](https://github.com/ksator/Machine_Learning_with_Python/wiki/About-the-Python-libraries-used-in-this-repo)  
+- [Euclidean distance vs Manhattan distance](https://github.com/ksator/Machine_Learning_with_Python/wiki/Euclidean-distance-vs-Manhattan-distance)  
+- [machine learning introduction](https://github.com/ksator/Machine_Learning_with_Python/wiki/machine-learning-introduction)  
+- [Introduction to arrays using numpy](https://github.com/ksator/Machine_Learning_with_Python/wiki/Introduction-to-arrays-using-numpy)  
+- [visualize a dataset using seaborn](https://github.com/ksator/Machine_Learning_with_Python/wiki/visualize-a-dataset-using-seaborn)  
+- [manipulate dataset with pandas](https://github.com/ksator/Machine_Learning_with_Python/wiki/manipulate-dataset-with-pandas)  
+- [classification using SVC (Support vector classifier)](https://github.com/ksator/Machine_Learning_with_Python/wiki/classification-using-SVC-(Support-vector-classifier))   
+- [Graph a dataset using matplotlib](https://github.com/ksator/Machine_Learning_with_Python/wiki/Graph-a-dataset-using-matplotlib)  
+- [Use k-Fold Cross Validation to evaluate the performance of a trained model](https://github.com/ksator/Machine_Learning_with_Python/wiki/Use-k-Fold-Cross-Validation-to-evaluate-the-performance-of-a-trained-model)  
+- [Remove irrelevant features to reduce overfitting](https://github.com/ksator/Machine_Learning_with_Python/wiki/Remove-irrelevant-features-to-reduce-overfitting)  
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