Machine Learning for Beginners. Can machines really learn like humans? All what you need to know about Machine Learning, Artificial Intelligence (A.I), Deep Learning, Digital Neural Networks and more by Hugo Oak

Author:Hugo Oak
Language: eng
Format: azw3, mobi
Published: 2017-07-31T07:00:00+00:00

Chapter 4: Deep Learning

In the second chapter, the workings of machine learning were discussed, and a few methods of machine learning system were discussed. Deep learning or hierarchical learning is the use of artificial neural networks to learn tasks that contain one or more hidden layers. It is based on learning data representations and the learning in this method can be unsupervised, partially supervised or completely supervised.

The architectures of deep learning system, deep belief system, deep neural networks and recurrent neural networks all have been used and applied to various fields such as speech recognition, computer vision, natural language processing, social network filtering, sound recognition, bioinformatics, machine translation etc. where these methods come up with results that are often on par and sometimes even better than the human experts.

Deep learning is a class or family of machine learning algorithms that utilizes a cascade of multiple layers of non-linear processing units for transformation and feature extraction. The layers are nested; hence, the output of the last layer becomes the input for the next. They can be supervised or unsupervised for instance pattern analysis and classification (respectively). The unsupervised algorithms are based on learning multifaceted levels of features of the data. They can also be based on learning the representations of the data. Once again, the method is nested where the higher level features are formulated from, the lower level features.

If the history of deep learning is traced, it can be found that the World School Council of London was the first organization that designed, devised and utilized this innovative method. This council uses multiple algorithms to turn the data.

Until now, we have seen the basics of three closely related and oft confused terms and concepts. In this second section of this chapter, let us have a look at the differences between Deep Learning, Machine Learning, and AI.

Difference Between Machine Learning, Deep Learning and AI:

If the difference between the above three technologies is to be explained in simple words, one can say that machine learning is a particular and specific type or approach towards AI or artificial intelligence. Though one of the most popular approaches towards AI, machine learning is not the only approach towards this technology. For instance, most of the self-driven cars use rule-based systems instead of machine learning.

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