14 Popular Machine Learning Evaluation Metrics

Thus far in our journey through Machine Learning Basics, we covered several topics. We investigated some regression algorithms, classification algorithms and algorithms that can be used for both types of problems (SVM, Decision Trees and Random Forest). Apart from that, we dipped our toes in unsupervised learning, saw how we can use this type of learning for clustering and learned about several clustering techniques. Finally, in the previous article, we talked about regularization and machine learning model performance. In all these articles, we used Python for "from the scratch" implementations and libraries like TensorFlow, Pytorch and SciKit Learn.