Both of these are advanced forms of technology. Machine learning evolved out of artificial intelligence, while deep learning is an evolution of machine learning itself. There is a significant difference between machine learning and deep learning.
Machine learning is an application and subset of AI (Artificial Intelligence) that provides a system with the ability to learn from its experiences and improve accordingly without someone physically programming those changes into it. Deep learning is basically a subset of machine learning that relates the recurrent neural networks and artificial neural networks together.
Read ahead to know more about the ways in which both of these differ.
What is Machine Learning?
It is an application and subset of AI (Artificial Intelligence) that provides a system with the ability to learn from its experiences and improve accordingly without someone physically programming those changes into it. Machine learning lets systems and devices improve without being programmed to that particular level. It makes use of data for training so that it can find some accurate results.
The primary aim of machine learning is to develop computer programs that access the required data and utilize it for learning by themselves.
What is Deep Learning?
It is basically a subset of machine learning that relates the recurrent neural networks and artificial neural networks together. Its algorithms are exactly like machine learning. The only difference is that the number of layers of algorithms used in deep learning is more than machine learning. All of these algorithm networks are together known as artificial neural networks.
In simpler words, every network of algorithms replicates just the way a human brain does- as all the networks stay connected (just like the brain). It is the exact concept used in deep learning. It basically assists in solving every complex problem using various algorithms and associated processes.
Difference Between Machine Learning and Deep Learning
Here is a list of the differences between Machine Learning and Deep Learning.
| Parameters | Machine Learning | Deep Learning |
| Definition and Meaning | It is an application and subset of AI (Artificial Intelligence) that provides a system with the ability to learn from its experiences and improve accordingly without someone physically programming those changes into it. | It is basically a subset of machine learning that relates the recurrent neural networks and artificial neural networks together. |
| Correlation | It forms the superset of the process of deep learning. | It constitutes a subset of machine learning. |
| Represented Data | The data that gets represented in this case is very different because machine learning makes use of unstructured information and data. | The data that gets represented in this case is also pretty different because deep learning makes use of ANN (neural networks). |
| Data Points | It contains thousands of different data points. | It consists of big data. It means that millions of data points are present in it. |
| Process of Evolution | Artificial intelligence evolves into machine learning. | Machine learning evolves into deep learning. In simpler words, deep learning refers to how deep/ detailed machine learning can get. |
| Outputs | It consists of numerical values, such as the classification of scores. | It consists of everything from the free-form elements (like free sound and text) to the numerical values. |
| Use of Algorithms | Machine learning utilizes a number of automated algorithms. These turn into various model functions for predicting future actions out of data. | Deep learning utilizes a neural network passing data through various processing layers. These interpret the features of the present data and their relations. |
| Detection and Depiction of Algorithms | Various data analysts detect and examine the algorithms for analyzing the specified variables present in data sets. | The algorithms present in deep learning basically undergo self-depiction on data analysis when they reach production. |
| Uses | Machine learning is capable of helping a system when it needs to stay in the competition while still learning new things parallelly. | Deep learning is capable of solving various complex issues that concern machine learning in a system. |
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