Pattern Processing – A Brief Guide to Machine Learning

From Hollywood portrayals of robots to consumer smart-home products, to transnational hacking societies, artificial intelligence (AI) and machine learning have been increasingly used by innovators and industries alike to accomplish amazing feats. It’s a tool that currently knows no bounds, and for this reason, it can be a little daunting to get our heads around. But utilising machine learning has a demonstrated track record of greatly improving the way we live our lives. Read on if you’re looking to unveil the mysteries of this often aggrandised practical tool.

Machine learning article image 883883831. Data analytics

AWS Australia and other data analysts and scientists, use data retrieved from AI technology to aid in the digital transformation of their clients’ businesses. In this age of information, the benefits of using AI in data analytics cannot be understated. As machine learning engages with – and thus enables enterprises to extract data from – a variety of sources, the amount of information that can be yielded by AI technology can be used to rapidly alter and finetune customer communication and engagement methods used by corporations. This means that machine learning can assist in developing a greater understanding of how to most effectively design websites and advertising, respond to customer feedback, and even how to organise sales for maximum results through providing you with a well-rounded picture of your industry’s financial climate. 

2. Identifying areas to improve efficiency

As AI technology interacts directly with your enterprise’s established processes, utilising machine learning will also provide you with an especially useful hands-on approach to simplifying your customer or user interface. Machine learning will enable you to see the step-by-step process through which customers will interact with your enterprise’s digital presence. It’s through the breaking down of this process that you’ll be able to identify any unnecessary steps to your processes, making your interface increasingly user-friendly for your customers, and increasingly efficient for both your client base as well as your employees. This increased smoothness will, in turn, provide you with a valuable edge up on your competitors.

3. Machine learning in security 

Machine learning has also been heavily used in the financial sector as a means of detecting fraudulent credit applications. The elegance of committing fraud lies in the ability of fraudulent applications to appear as authentic. People can commit fraud consistently across a variety of financial agencies from banks to internet service providers, and go years without their claims raising any brows. With that said, the difficulties surrounding detecting financial fraud are rapidly becoming a concern of the past. This is thanks to the utilisation of machine learning as a means of catching inconsistencies in data surrounding credit or loan applications and bank accounts.

4. Overall innovation

Finally, if you’re still not convinced that AI is our friend rather than our enemy, look no further than the consumer goods that have taken the market by storm over the past decade. AI has found its way into our smartphones, enabling everything from camera filters and lens variation, and facial and fingerprint recognition, to battery optimisation and wireless charging, and augmented reality features. Even hobby products like drones, programmable robots and MIDI controllers, have all utilised AI technology as a means of developing a more sophisticated user interface. And the icing on the cake? The incorporation of AI in the automotive industry which is set to propel us into the future we’ve been waiting for since Marty McFly first hit the big screen.

AI technology is being utilised wherever it can, simply because the insights it has offered us have been incredibly useful regardless of which industry or sector you’re operating in. As hackers and other similar local, national, or international security concerns are also using AI to further their own independent causes, it makes sense for governments and enterprises alike to invest in machine learning themselves as a means of ensuring our processes are well-established and secured.