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+Building intelligent machines to transform data into knowledge
+The three different types of machine learning
+  Making predictions about the future with supervised learning
+    Classification for predicting class labels
+    Regression for predicting continuous outcomes
+  Solving interactive problems with reinforcement learning
+  Discovering hidden structures with unsupervised learning
+    Finding subgroups with clustering
+    Dimensionality reduction for data compression
+An introduction to the basic terminology and notations
+A roadmap for building machine learning systems
+  Preprocessing – getting data into shape
+  Training and selecting a predictive model
+  Evaluating models and predicting unseen data instances
+Using Python for machine learning
+  Installing Python packages
+Summary