Making the move from Predictive Modelling to Machine Learning

If you visit the data science competitions website Kaggle, the example problem that they have for new starters is predicting the survivors and non-survivors from the Titanic from a sampled training dataset. This training dataset contains various attributes of the passengers, like the passenger's ticket class, the boarding gate, number of siblings, age, gender, etc. One can build a model using whatever tool you prefer and test your algorithm on a sample and see how you faired against the best of the best. Don't be disillusioned if your model only comes out at 76% accuracy against the winner's 100%. One can just Google the actual names and see who lived and who did not.