In recent times, both the terms ‘machine learning’ and ‘deep learning’ are creating a huge buzz around the AI landscape. The world is steadily becoming an artificial intelligence-first one where digital assistants together with other services act as our primary source of information. This concept is backed by the two terms we just mentioned. Both deep learning and usual machine learning are methods of teaching AI to perform tasks.
Over the past few years, you probably have observed the emergence of high-tech concepts like deep learning, as well as its adoption by some giant organizations. It’s quite natural to wonder why deep learning has become the center of the attention of business owners across the globe. In this post, we’ll take a closer look at deep learning and try to find out the key reasons behind its increasing popularity.
In recent years, artificial intelligence and big data have offered a significant number of advantages to businesses together with some new terminologies that every aspiring tech enthusiast should have a clear understanding of. Deep learning and neural networks are two such terms which are often interchangeably used by many people. But in reality, they’re not the same thing. In this post, we’re going to take a closer look at these two to help you develop a proper understanding of them.
If you’re interested in learning artificial intelligence or machine learning or deep learning to be specific and doing some research on the subject, probably you’ve come across the term “neural network” in various resources. In this post, we’re going to explore which neural network model should be the best for temporal data.