Machine Learning (ML) is often seen as somewhat intimidating and difficult subject if one doesn't have previous exposure to math, statistics, probability, numeric analysis, and similar topics. Unfortunately this leads to many people never trying it, while the world is in need of more ML engineers. This talk aims to demonstrate how easy it is to get started with ML and train powerful models that can solve real-world tasks. All this can be done without heavy maths background, by building on the existing technology, pretrained models and community knowledge. Similar to how web frameworks such as Django make application development easier, there are now several popular ML frameworks such as Keras and PyTorch. They free you from low-level math-intensive coding tasks, and instead make it easy to focus on the higher-level aspects of the problems you're trying to solve. The author got started with machine learning less than 1 year ago, after years of doing web development with Python and Django. This talk chronicles that journey and hopefully encourages others to try the same.