How is ai data science used in interpreting data?

Asked by Ronak Sharma over 1 year ago

Answers 1
ayush sharma

ayush sharma

Economics Undergrad Student || dep. Marketing Head at Enactus ARSD

It’s a very good question, but a little complex to relate to. Because artificial intelligence (AI) is basically integrated into data science. The simplest answer can be; via algorithms and analytics. The main process is to set up what you do to make it work. Because same as the name AI, in data science it is only as good as the data it is fed on.

Let me explain it in simpler terms. Artificial intelligence basically works with the help of machine learning algorithms. You have to understand machine learning if you wish to understand how AI data science is used in interpreting data. We all know that AI is a subset of machine learning. Quick explanation; machine learning is the use of computer systems that can learn and adapt to work with no or minimal human interference.

This was important to know because data science interprets data completely relying on machine learning and AI. The definition may have seemed like AI itself, no? It's because it is, just with a few tweaks. In data science, many algorithms are used to work on data. Generally the use of AI is there to make the work more accurate and faster. Going on a project again and solving is not an option with big data samples.

In these situations, data scientists basically prepare analytical codes and algorithms that filter out data samples on their own. AI data science automatically analyzes data and finds out what is needed. It can be a pattern, helpful insights, any figures or something that is needed. If you want to know it more deeply, it uses Natural Language Generation, which is a technique of presenting information in a different way (that is understandable).

When there are large data samples, a lot of algorithms are set to filter out the information and fixate on certain things. It's like using keywords to find your desired things on the internet. AI-powered systems basically analyze data and find what also right is set. This is why many people believe that AI can learn and be developed on its own while some don’t. Because if it can, why does it need certain algorithms? Well, this question is for some other time.

All these things don't mean that codes and algorithms are the backbones here. Because AI can dive into data and analytics on its own (given that it has been programmed that way). So you can use it on different sets of information without adding any more things to it. Whether it is to interpret data and find value or just to browse. Does this help your question or did I misinterpret something? Well, I’m not as accurate as AI but feel free to ask anything on this.


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