Decoder: Machine Learning vs Deep Learning

Although they are both important and "buzzy" technologies of the 4th Industrial Revolution and both involve some sort of "learning", deep learning and machine learning are not interchangeable terms and have very significant and unique differences which set them apart from each other.

Let's start off with machine learning. Machine learning means computers learn from data using algorithms to perform a task without being explicitly programmed. It is the intersection of computer science and statistics where algorithms are used to perform a specific task without being explicitly programmed; instead, they recognize patterns in the data and make predictions once new data arrives. The learning process of these algorithms can either be supervised or unsupervised, depending on the data being used to feed the algorithms.

Machine learning supports a lot of automated tasks that span across multiple industries, from data security firms that track down malware to finance professionals who want alerts for favorable trades and a wide array of other use cases. The algorithms are programmed to constantly learn and get better at predicting the patterns which are to be modeled.

Deep learning, on the other hand, is considered an evolution of machine learning. It describes algorithms that analyze data with a logic structure similar to how a human would draw conclusions. How do the algorithms do this?  Well, by using a programmable neural network that enables machines to make accurate decisions without help from humans. The programmable and artificial neural network is inspired by the biological network of neurons in the human brain, leading to a learning system that’s far more capable than that of standard machine learning models. 

Like other types of Artificial Intelligence, deep learning requires lots of training to get the learning process on lock. This requires vast amounts of data as well as computing power to accomplish. But once that's out of the way, functional deep learning is a marvel that is considered by many to be the backbone of artificial intelligence.

In conclusion, it is important to note that both machine learning and deep learning are subsets of the field of Artificial Intelligence. Furthermore, it is also important to know that deep learning itself is also a subset of machine learning. With that said, both technologies are a vital and core part of the 4IR and will continue to get better as computing power improves and digitization initiatives avail data that can be used in the training of the algorithms that drive these technologies.

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