Summary

I hope you enjoyed this last chapter of an exciting tour of machine learning. Throughout this book, we covered all of the essential topics that this field has to offer, and you should now be well equipped to put those techniques into action to solve real-world problems.

We started our journey with a brief overview of the different types of learning tasks: supervised learning, reinforcement learning, and unsupervised learning. We discussed several different learning algorithms that can be used for classification, starting with simple single-layer neural networks in Chapter 2, Training Machine Learning Algorithms for Classification. Then, we discussed more advanced classification algorithms in Chapter 3, A Tour of Machine Learning Classifiers Using Scikit-learn, and you learned about the most important aspects of a machine learning pipeline in Chapter 4, Building Good Training Sets – Data Preprocessing and Chapter 5, Compressing Data via Dimensionality Reduction. Remember that...