So, You Are Interested In Deep Learning

So, You Are Interested In Deep Learning

Deep learning has a place in several industries and applications. In this article, there is an evaluation of the applications of deep learning, including types of problems deep learning techniques can solve.

What Is Deep Learning?

Deep learning is a subfield within machine learning that is concerned with the utilisation of artificial neural networks(ANNs) to learn patterns within data.

The knowledge within ANNs is utilised for solving tasks that share a close association with the data the ANNs are trained on.

The relationship between deep learning and artificial intelligence lies in the fact that the learning process and feature extraction within deep learning architectures occurs automatically. Learning is driven by logical units referred to as neurons that are designed to mimic the biological neurons within the human brain.

Hence, deep learning enables the development of artificially intelligent systems.

Deep learning has a place in several industries and applications. In this article, there is an evaluation of the applications of deep learning, including types of problems deep learning techniques can solve.

Emergence

As previously stated, deep learning is a subfield of machine learning.

Machine Learning as a field is concerned with the development of algorithms that learn automatically without any explicitly defined instructions on how to ‘learn’.

Before the introduction of deep learning, traditional machine learning techniques involved a very hands-on approach.

Prior to the widespread adoption of deep learning, machine learning researchers and engineers had to engineer algorithms to detect specific features to be extracted. These features described objects and provided contextual information within the images.

The method by which machine learning practitioners, pre-deep learning era, defined features to be extracted was cumbersome. The process involved the analysis of the input, output and intermediary processes within the system to be developed.

The task of feature engineering within traditional machine learning algorithms was not scalable.

The introduction of deep learning enabled the ability to learn explicit patterns and features directly from the input data. The requirement of creating handcrafted algorithms is obsolete when utilising deep learning for developing machine learning systems.

deep-learning

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