Data Analytics
What is it?
Machine Learning
& Deep Learning
While Machine Learning and Deep Learning (ML/DL) is often seen as a sub-category of Artificial Intelligence (AI), it would be correct to think of it as the current state-of-the-art of AI – ML is currently showing the greatest potential in providing tools to industries and societies to drive change. Machine Learning is an approach to AI showing great potential when it comes to developing autonomous, self-learning systems which are revolutionising and disrupting many industries.
In the simplest way possible, a Machine Learning algorithm is trained from a specified ‘training set’ of data which is then used as the basis to solve a given problem. An example of this would be when a computer is given a training set of photographs, some which say “this is a flower”, and some which indicate “this is not a flower.” Next you would show the computer a series of new images and it would start to distinguish which photos contain flowers.
Machine Learning continuously adds to its date set by identifying every picture (correctly or incorrectly), essentially becoming ‘smarter’ and more efficient at completing tasks over time. It is, in effect, learning.
Deep Learning (DL), on the other hand, can be considered as the ‘cutting-edge of the cutting-edge.’ Essentially, DL fuses AI’s core ideas and revolves them around solving real-world problems with deep neural-networks designed to mimic our own decision-making. It is easiest to describe Deep Learning as a sub-set which focuses on narrower tools and techniques, applying them to solve just about any problem which requires ‘thought’ – human or artificial.
How we use Machine Learning
& Deep Learning
Data Modelling
Looking at existing data to predict what is likely to occur and what is going to occur.
Process Automation
Industry-leading model-building, automation and evaluative capabilities.
Computer Vision
Classifying data in a method that is otherwise hugely time consuming and often complicated
How is it used?
Why is machine learning and deep learning being used?
From our experience, Deep Learning is being constantly implemented into businesses at a significant rate over the last few years which we believe could be to its outstanding ROI capabilities and insights. We come across many shapes and forms of DL on a daily basis. For example, Deep Learning is used by Google in its voice and image recognition algorithms, used by companies such as Netflix and Amazon, to help their users in deciding what to watch or purchase next, and even by researchers at MIT to predict future economic occurrences. By being able to provide powerful and unrivalled insights, predictions and decision making in potentially any industry, ML and DL are considered as invaluable and irreplaceable by many organisations.
Applications
Machine Learning & Deep Learning In Industry
Predictive analytics is allowing both SMEs and large organisations to become proactive and forward-looking through the anticipation of outcomes and behaviours, based on the collation of data. Prescriptive analytics can be taken one step further. Based on predictive analytics, prescriptive analytics conducts the optimal decision-making to provide suggestions for businesses to capitalise from their predictions or protect themselves from any arising implications. These tools help you gain a competitive advantage by discovering patterns in data and going beyond knowing what has happened, to anticipating what is likely to happen next.