Data Science, AI, ML and Deep Learning?
Have you ever asked yourself what Data Science is and how it is actually related to topics like Artificial Intelligence, Machine Learning or Deep Learning??
Well, here is a quick answer:??
But let’s explain it now:??
Data science is all about data and we use it to make business decisions. Data is revenue: indeed, the more data you have, the more business insights you can generate. Companies are using data science to build recommendation engines, predicting user behavior, and much more.?
Now that we understood this, what are the subsets of AI that we might know??
Machine Learning (ML) is considered a sub-set of AI. So, whenever you think about AI, you can think of applying ML there. As the name makes it pretty clear, ML is used in situations where we want the machine to learn from the huge amounts of data we give it, and then apply that knowledge on new pieces of data that streams into the system.??
How does a machine work, you might ask???
Well, there are many types of machine learning:?
In some of these methods, a user tells the machine what are the independent variables (input) and which is the dependent one (output). ?
This way, the machine learns the relationship between the independent and dependent variables present in the data that is provided to the machine. ?
Even though ML is super powerful for most applications, there are situations where ML leaves a lot to be desired: that is where deep learning steps in. ?
Indeed, if you have huge amounts of data on which you can train a model, and if the data has too many features, you take the deep learning (DL) route. ?
Nonetheless, deep learning requires much powerful hardware to run on. ?