wrapping up you now know how to apply the important machine learning algorithms for supervised and unsupervised learningwhich allow you to solve wide variety of machine learning problems before we leave you to explore all the possibilities that machine learning offerswe want to give you some final words of advicepoint you toward some additional resourcesand give you suggestions on how you can further improve your machine learning and data science skills approaching machine learning problem with all the great methods that we introduced in this book now at your fingertipsit may be tempting to jump in and start solving your data-related problem by just running your favorite algorithm howeverthis is not usually good way to begin your analysis the machine learning algorithm is usually only small part of larger data analysis and decision-making process to make effective use of machine learningwe need to take step back and consider the problem at large firstyou should think about what kind of question you want to answer do you want to do exploratory analysis and just see if you find something interesting in the dataor do you already have particular goal in mindoften you will start with goallike detecting fraudulent user transactionsmaking movie recommendationsor finding unknown planets if you have such goalbefore building system to achieve ityou should first think about how to define and measure successand what the impact of successful solution would be to your overall business or research goals let' say your goal is fraud detection