What is Machine Learning and how does it work? But even more importantly, what problems can ML solve for you and your company? Once you have understood the potential use cases, we will briefly describe the main challenges in the world of Big Data. Why is deploying ML models so hard and how can Cloud Computing help? Many MLaaS options are available on the market (AWS, Google, Azure, BigML, etc.). We will see how they compare to each other and which may best fit your needs. Whenever MLaaS is not enough, you can build your own ML models. We will briefly explain why Serverless is a great deployment strategy for this use case and what problems and limitation arise with it. Furthermore, we will put these ideas into practice and build a model for Sentiment Analysis, based on Python (scikit-learn), and trained with a public dataset by Stanford University.