Machine Learning: How AI Learns

Luke Frost our consultant managing the role
Author: Luke Frost
Posting date: 7/4/2019 8:47 AM
Amazon has begun curating summer reading lists. How? Patterns. Facebook shows you ads for items you may have been searching for online. How? It learns from your browsing habits. Ever wondered how Facebook knows you were just looking at that pair of shoes or that particular guitar. The Data you feed it, feeds its brain. In other words, this is how Artificial Intelligence learns. Machine Learning.

Whilst it can be disconcerting to know that a machine understands our buying habits, that’s not the only thing it’s used for. It’s also a pivotal tool in such areas as Bionformatics, Biostatistics, Computational Biology, Robotics, and more. 

What is Machine Learning?


Ultimately, it’s a method of Data Analysis which helps to automate model building and is part of Artificial Intelligence. In other words, it helps to solve Computational Biology problems by learning from Data to identify patterns and make decisions with little human intervention.

This helps scientific researchers learn about many aspects of biology. However, running a Machine Learning project can be difficult for beginners, who may experience issues when trying to navigate the information without making mistakes or second guessing themselves. This is one of the reasons a Computational Biologist might want to upskill with a course or two in Machine Learning for a more robust understanding of the information being learned and applied. 

The Good News and the Bad


With each shift of industrial revolution, there has been one system which has made an indelible mark on our daily lives and the Fourth Industrial Revolution is no different. Just like we can no longer imagine factories without assembly lines, we can also no longer imagine not having Siri, Google Maps, or online recommendations. But, as exciting and as important as these things are, Machine Learning has become so crucial to our daily lives, so complex, it takes a technology expert to master it leaving it nearly inaccessible to those who could benefit from it.

Why is Machine Learning Important?


By building models to peel back the layers and discover connections, organisations can more easily and more quickly make improved decisions with little to no human intervention. Computational processing is both more affordable and more powerful. It’s possible to quickly scale and produce models which can analyse bigger and more complex data and there’s also a chance to identify opportunities and to help avoid any unknowns such as risk.

Machine Learning is used in every industry from Retail to Financial Services to Healthcare. Here are just a few ways it has already transformed our world.

  • Retail – Retailers are able to learn from their customers buying habits, predictive buying habits, how to personalise a shopping experience, price optimisation, and customer insights.
  • Financial services – Machine Learning helps to prevent fraud and identify Data insights.
  • Healthcare – Wearable devices allow for real-time data to assess a patient’s health. Medical professionals can also more quickly find red flags which can help improve diagnoses and treatment.
  • Oil and gas – It cannot only help find where oil might be, but also predict refinery sensory failure, and streamline distribution.
  • Transportation – Help to make routes more efficient and predict problems that could affect the bottom line. While humans can create at least one or two models a week; Machine Learning can create thousands. 

Ultimately, the goal of Machine Learning is to understand the structure of Data. As it learns to determine what Data is needed for its structure, it can be easily automated and sift through Data until a pattern is found. This is how machines learn.

If you’re looking to take your next step in the field of Machine Learning, we may have a role for you. Take a look at our latest opportunities, or get in touch to see if we can help you take that next step.

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Three Ways Data Impacts The Customer Experience

In 2019, over 50 per cent of companies had adopted Big Data, with a further 38 per cent citing that they would be investing in it in the future. As it stands, we can assume that now, at least three-quarters of businesses will have invested in Big Data capabilities. By 2022, the annual revenue from the global big data and business analytics market is expected to reach $274.3 billion.  The lucrative nature of this industry stems from a recognition by many companies that it’s no longer good enough to guess what customers might want or need from your product or service, but to have hard evidence to back up your choices. Not only does this make for much happier, more satisfied customers, but it undoubtedly improves the bottom line.  Here are three examples which showcase how Data can positively impact the customer experience: 1. Create a more intuitive website journey From heatmapping the areas of interest (or disinterest) on your website through eye movement or mouse tracking to traffic analysis through tools such as Google Analytics, Data can give you both real-time and overall information about the success of your website.  You can analyse areas of the website where consumers ‘linger’ or click through, such as content pieces, links or assets, which proves to give added value or entice them to learn more about your business. You can also see areas where little to no activity happens, allowing you to create a new, perhaps more engaging, strategy.  The use of data for website ensures your get the design and content right in less time. The cost of redesigning a website can be a hefty cost for any business. The fewer times a website needs chopping and changing, the more cost-effective it will be, not forgetting to mention a much smoother and more efficient process for customers. 2. Building loyalty through personalisation In a report featured in Forbes by The Harris Poll, 76 per cent of Americans are more likely to complete a purchase if the customer journey has been personalised to them, their needs and wants. The story is similar in the UK, 80 per cent of companies report seeing an uplift after employing personalisation tactics.  However, personalisation must go one step further than just addressing a person by name in an email nowadays. It means targeting consumers with specific and relevant ads that actually take their interest instead of bombarding them with a scattergun approach, as well as looking at areas such as location-specific targeting and device optimised outreach. This can be made possible by combining marketing data, such as brand interactions, combined with sales data, previous purchases, and customer service data, the feedback given. These aspects allow you to create an in-depth and meaningful customer journey map, help you understand what turns specific consumers on, or off, and ensures your marketing messages and outreach are pertinent.  3. Be prepared for problems before they occur Data can give incredible insight into what’s working currently for a business but, arguably, its strengths lie in giving accurate understanding into the potential risks or problems that are likely to occur in the future.  According to Clarion Tech, there are seven areas in which Data can play a crucial role in minimising risk, errors or issues for a vast range of businesses. From making sense of unused business data to making companies proactive instead of reactive, minimising misleading forecasts to diminishing customer service challenges, data can be the solution to a wealth of problems.  Not only do these kinds of errors leave a bitter taste in the mouths of customers who may struggle to revisit your business after a bad experience, but they can negatively affect your bottom line too. Nipping them in the bud before they happen is an incredible card to have to hand, and one that could be the saviour of your business.  To learn more about how working with a Data & Analytics specialist could help bolster the success of your business, contact our team or, if you're looking for your next opportunity, check out our latest roles. 

Data Science For Business Decision Making

All strong and successful businesses are built and run upon well-informed decision-making, which derive from a mix of leader experience, industry knowledge and, more recently, the regular implementation and use of advanced Data Science teams.  While the use of data has been around for many years, it’s hard to believe that it is only in the last five years or so that we have seen the adoption of such technology and skills really take off. Five years ago, the importance and demand for Data Scientists sat at a very meagre 17 per cent, whereas in 2019, we saw exponential growth of over 40 per cent – a number that is expected to continue growing as we move forward.  Within Data & Analytics, Data Science is a crucial arm within many businesses of all shapes and sizes. Through the collection and analysis of certain datasets, Data Science teams can delve into an organisation’s pain points, any potential obstacles and future predictions; crucial elements which, if looked at and planned for in advance, can be the making of a business.  So, how else can Data Science influence the decision-making process and make a positive impact on a business and its bottom line? The removal of bias and the increase of accuracy As humans we are innately susceptible to bias, conscious and unconscious, and this can be a hindrance on our ability to make informed yet impartial decisions. By relying solely on facts and figures instead of our own opinions, we are not only removing bias, but we are in turn making the decision-making process more accurate.  Accuracy within decision-making will remove the potential risk of mistakes and the need to re-do tasks, therefore saving precious time, resource and money, unequivocally a benefit for any business’s bottom line.  Efficiency There are elements of all businesses that require trial and error for example, hiring practices. People who look great on paper and perform exceptionally well in first interview may turn out to be utterly the wrong fit six months down the line. However,  collecting and recording data of those employees who do fit well into the business, compared to those who don’t, can help to reduce the chance of choosing the wrong candidate. This in turn improves staff retention rates, helps create a positive work culture and, of course, positively impacts profitability.  Considering the cost for hiring one person for a company is around £3,000, Data Science is of huge benefit to any company, large or small, in reducing the risk of high staff turnover.  Mitigating risk All businesses at some point in their lifetime will come up against potential obstacles and risks that, if not managed properly, can be potentially lethal. The implementation of Data Science will allow senior leaders to learn from past mistakes and create evidence-based plans to better tackle, or completely avoid, similar problems in the future.  This could be for either organisational risk or strategic risk, both of which can be extremely damaging if not prepared for. Organisational risk entails problems occurring within daily business tasks such as fraud, data loss, equipment and IT issues and staff resignations. Strategic risk relates to events that cannot be planned for in advance; those sudden and unforeseeable changes - a great example being the current COVID-19 pandemic.  However, with both risk groups, Data Scientists can help to mitigate these risks through learnings and observations made from reams of previous data, as well as real-time intelligence. This allows senior leaders to act fast where needed, and plan where possible.  Data & Analytics, and especially Data Science, has been, and will continue to be, a key driver in the evolution of many industries worldwide. As we move forward, we will undoubtedly see an even larger uptake of the available technologies as business leaders everywhere begin to see the influential value of data-driven decision-making. If you’re a Data Scientist looking to take a step up or are looking for the next member of your team, we may be able to help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.

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