What are Machine Learning and Deep Learning? The concept of artificial intelligence in other words, the idea of that a machine can learn and think for itself has been around since the middle of the last century.
The term was coined by a group of American scientists John McCarthy, Marvin Minsky, Allen Newell and Herbert Simon in a paper they presented at a conference held in Dartmouth College, USA in 1956.
Fast-forward to 2021 and artificial intelligence and its subfield of machine learning are part of our everyday lives. Indeed, AI is used by a growing number of organisations and research centres worldwide, in a huge range of applications and products from chatbots to healthcare, cybersecurity to automobiles.
Machine Learning uses numerical and statistical approaches to encode learning into mathematical models, which are then used to make predictions on new data, situations and scenarios.
The most cutting-edge branch of ML is Deep Learning, which is based on very deep and complex artificial neural networks, usually referred to as deep neural networks, which essentially try to emulate the human brain’s learning abilities.
In deep learning, the first few layers of the network perform feature extraction in a series of stages, just as the brain seems to do. The level of complexity and abstraction of such features increases through the network, with the actual decisions taking place in the last few layers of the network structure.
Deep Learning is an extremely exciting development that has sparked an AI revolution in many aspects of our life, and is the key technology behind the recent spectacular developments in fields such as biomedical signal analysis, image recognition, driverless cars, speech processing and natural language processing.
Why study Machine Learning and Deep Learning?
It is a growing field offering exciting career opportunities for those who have studied the subject at university and gained the necessary skills.
Not only the big tech companies, but also medium and small enterprises are embracing this AI revolution, and are incorporating machine learning in the products and solutions, from the financial sector, to security and defence, to medical and manufacturing.
Based on this, the job market has seen a considerable increase in the demand for data scientists and analysts, machine learning experts and developers.
How to get started in Machine Learning and Deep Learning
Students who want to focus on this science should look for a relevant programme that provides the necessary skills and knowledge to be able to design these systems and ideally feature Deep Learning as a significant aspect of the programme.
Such programmes should focus on the algorithms and state-of-the-art novel engineering and software technologies required for machine learning and deep neural network systems.
While some may see such systems as obscure black boxes that sometimes make strange decisions, researchers are working hard toward developing “explainable AI”, where the decisions made by machine learning algorithms are traced back to the data, to fully understand their rational.
But to achieve this, a complete understanding of the algorithms and techniques underpinning such complex machine learning and deep learning architectures is paramount.
Therefore, the emphasis should be on architectures, algorithms and implementation with applications in a diverse range of areas: basic data analytics and big data technologies, machine learning and decision-making algorithms, digital signal processing principles, use of programming languages such as Python.
Career opportunities in Machine Learning and Deep Learning
As the demand for AI and machine learning has increased, organisations require professionals with complete knowledge of these growing technologies and experience.
For those who acquire skills in machine learning and deep learning, there are a wide range of jobs in multinational corporations across India and the world in various, including as software engineers, electronic engineering systems analysts, data scientist or engineer and data insight analysts.
Graduates with degrees that provide a unique skillset useful in a broad range of application sectors will be very likely to succeed in securing the most sought after jobs.
– Article by Dr Gaetano Di Caterina, Course Director of MSc in Machine Learning and Deep Learning, Lecturer in the Department of Electronic and Electrical Engineering, University of Strathclyde, UK
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