About the Deep Learning category


(Jeremy Howard (Admin)) #1

Use this category to discuss anything to do with deep learning that’s not related to a fast.ai course (each of those has its own category) - including stuff that’s not related to fast.ai at all!

Topics could include new papers, projects, applications, recent news, or anything else you’re interested in!


(Maxim Pechyonkin) #2

This is really good news. Sometimes I have a question but it is not directly related to anything that was taught in the courses. Now there is a good place to ask.


(Su Wei) #3

This is a good place to search unfamiliar topics about deep learning.

Thanks.

:yum:


(Preethi Shetty) #4

May I know what is the difference between Deep Learning and Machine Learning?
Does they both are related to Data Science or Artificial Intelligence?


(vinod kumar) #5

Understanding how artificial intelligence works may seem to be highly overwhelming, but it all comes down to two concepts, machine learning, and deep learning. These two terms are usually used interchangeably assuming they both mean the same, but they are not. Both the terms are not new to us, but the way they are utilized to describe intelligent machines has always been changing.

Difference Between Machine Learning and Deep Learning

It is important for organizations to clearly understand the difference between machine learning and deep learning. By definition, machine learning is a concept in which algorithms parse the data, learn from it, and then apply the same to make informed decisions. A simple example would be of Netflix, which uses an algorithm to learn about your preferences and present you with the choices that you may like to watch.

In the case of machine learning, the algorithm needs to be told how to make an accurate prediction by providing it with more information, whereas, in the case of deep learning, the algorithm is able to learn that through its own data processing. It is similar to how a human being would identify something, think about it, and then draw any kind of conclusion.

Hope you understand the concept.

Thank you.
vinod kumar kasipuri.