This was the presentation for the Microsoft Community Technology Update of 2016. The idea was to introduce to people the concept of Machine Learning and its easy to get started if you are keen. My objective was also to communicate how some of the algorithms work and they require no more than basic understanding of Math to get going, sometimes not even that. The algorithms we covered were, Support Vector Machines (SVM), Decision Tree using R2D3 and Neural Networks for classification. We used the Tensorflow Playground to help understand the Neural Network and Deep Learning concepts. I gave an analogy of how Machine Learning process is like making a smoothie where your algorithm is a recipe, your data are your ingredients, your computer is your blender and your smoothie is the model that you developed. I used the same example to convey the concept of Training Validation and Testing. Coverage of Type 1 and Type 2 errors together with the metrics of Recall and Precision was covered as well. Finally I closed the session with what are some good resources to get started with Machine Learning for all skill levels. There are references to websites, courses, kaggle competition, podcasts, cheat sheets and books.