Artificial Intelligence v/s Machine Learning v/s Deep Learning
Machine Learning, Artificial Intelligence, and Deep Learning essentially do the same thing, i.e., automating tasks usually performed by humans.
More specifically, taking in input and giving the desired output.I’ll explain the relationship between the three using the following graph.
As you can see, Machine Learning is the subset of Artificial Intelligence, and Deep Learning is the subset of Machine Learning.
Artificial Intelligence
It’s a comprehensive set consisting of any task that simulates human intelligence. Essentially a machine doing a job previously done by humans. It can be anything from computers and robots to tallies and abacus. Because of this, I’ll change our definition to suit our field of data science better.
Artificial Intelligence is the use of Mathematics and Computer Science to solve tasks generally done by humans.
This definition better suits our intentions going forward. It includes simple computer programs and complex neural networks designed to solve problems usually done by humans.
Machine Learning
Machine Learning is using machines to learn from data without being explicitly programmed. It has the highest paced growth in the field of Computer Science. As evident from the name, it gives the computer that makes it more similar to humans: The ability to discover patterns. Machine learning is being actively used today, perhaps in many more places than one would expect, from writing tools to self-driving cars.
Deep Learning
Although a new field, it shows great promise in solving highly complex problems worldwide. It is a topic I am highly passionate about, so I might be biased : /. Thanks to the recent changes in computing, like graphic processing, the field has been growing rapidly. With the massive growth of data, the importance of Deep Learning and its research has become evermore apparent. To find out more about this topic check my previous stories.
Conclusion
As you can see in the above graph, the interest and scope in the fields as been growing at a rapid pace, and the world has taken notice of both the good and the bad. Our job as Data scientists is to address these concerns and help in the development of the field.
