Making sense of deep learning
Deep learning is a type of machine learning that is able to work with image, video, audio and natural language data.
Ok, so what is machine learning? In a nutshell, it’s a group of techniques that allow computers to come up with a way to solve a problem by themselves only by looking at data, rather than being pre-programmed with a set of answers as is the case in software development.
For example, in traditional software development if you wanted to create a solution that is able to detect whether there is a car present in an image or not, you would have to explain (code) how a car looks from every possible angle and in every possible color, shape, lighting conditions, background, and countless more variables. This wouldn’t be humanly possible.
Instead, with machine learning (and specifically deep learning since we’re talking about images in this example) you can show the computer thousands of car images and let it analyze them by itself to look for patterns. By repeatedly doing this, it begins to recognize the features that make up a car and develops a model of how a car looks like. Once it has built this model, next time it comes across a car picture it should be able to identify it.