As AIs progress, the limits between robots and humans are narrowing. AI challenges us in countless areas and is surpassing our ability to complete countless tasks.
And today, companies want us to talk to them via AI–their so-called vocal assistants.
As if talking to a robot has become normal!
Recent years have seen an explosion in so-called conversational AI. The problem is that some current systems are still unstable and don’t exactly spark the desire for conversation.
Conversational agents have a poor reputation. They have only an average sense of humor, problems with understanding humans, and slow execution.
Overfitting is a very comon problem in machine learning. It occurs when your model starts to fit too closely with the training data. In this article I explain how to avoid overfitting.
Overfitting is the data scientist’s haunt. Before explaining what are the methods that we can use to overcome overfitting, let’s see how to detect it.
No, it’s not about Terminator…
A lot is said about machine learning. Some perceive it as a monster that is leading humanity to its doom. Others perceive it as a magician who solves all their illness. In reality it’s much simpler than that (and a little bit less scary).
Machine learning is a technique that allows automatic systems improvement using data.
The amount of data explosion and the progress in processing and storage techniques, have help machine learning to establish in many areas.
Behind this mysterious name hides a very simple concept. To learn, the system is inspired by existing…
HEY! I am Ilyes. Student in machine learning and french bloger. I will help you to discover the world of AI :)