What is the difference between Deep Learning and Machine Learning?
Even though gaining understanding on how artificial intelligence works might be overwhelming, there are two main concepts that can aid you in gaining understanding of the process: machine learning and deep learning.
Both machine learning and deep learning are terms frequently used in relation to Artificial Intelligence. The core difference between the two is that machine learning represents the science of determining the machines to mimic humans without the need of programming, while deep learning is a subgroup of it.
It is very important to understand the difference between the two concepts due to the fact that they are slightly different. Machine learning represents a concept in which algorithms get the data, learn from it and apply it in order to make informed decisions.
For machine learning, the algorithm is required to be told in what manner to establish an accurate prediction by offering it more data. In the case of deep learning, the algorithm is able to undergo the learning process through its own data processing. In some aspects, the whole process resembles how a human being would solve a problem and draw conclusions.
Machine learning employs automated algorithms which learn how to predict future decisions and determine functions depending on the data set they had, whereas deep learning is more complex. Deep learning interprets the data set, along with its relationships within the data by using neural networks in order to analyse the relevant data through various stages of data processing.
The multitude of algorithms used in machine learning are conducted by the analysts with the purpose to examine different variables in the data set. For deep learning, the algorithms are implemented and self-directed for proper data analysis. Moreover, for deep learning the output can consist of anything ranging from a score, free text or sound, while for machine learning the output is in most of the cases a numerical value such as a score or classification.
When it comes to the time required, deep learning needs more time to train as compared to machine learning. The issue is the fact that there are a multitude of parameters used in a deep learning algorithm. Machine learning is faster, ranging from a couple of seconds to a couple of hours.
Anyhow, both deep learning and machine learning have multiple purpose and are applied in a variety of real-life situations. Computer vision, information retrieval, marketing or medical diagnosis are all fields in which both are used to provide accurate data.