Since 2012, with the proliferation of Python in general software development, Machine Learning has become the biggest trend in the technology world. Because of the many applications that ML could have within every business, it’s quite easy to understand why the topic is so heavily looked after. With applications ranging from the mobile world to the automotive industry, let’s break down Machine Learning in its complexity.
Why Automation Is Important
Machine learning as a matter it’s appealing because it proposes as an automated form of management for both infrastructures and digital tools. The brightest example would surely be related to warehouse management and production, where robots are the majority of the entire chain. In this case, a Machine Learning coded program could definitely be implemented in terms of management: the tool, installed in the central brain, could heavily optimise the entire production chain.
On the other hand, automation is as fragile as it could be: a simple error in the mainframe could cause a series of cascade malfunctions, naturally leading the entire production process to the end.
The Mobile Sector
Smartphones have been taking over the world since the launch of the first iPhone. Many mobile app development companies, in fact, are heavily working on different Machine Learning algorithms, in particular, the ones that are UX (User Experience) focused.
Applications like Alexa’s voice search, for example, have been incredibly popular from a development point of view, given the fact that Voice Search Optimisation will be potentially the biggest thing in the near future.
When it comes to personal finance and mortgages, there is a variety of tools available online which are calculating requirements, status and projections. An interesting case study would be related to bridging loans, given the fact that fast-paced finance is heavily looked after by many clients. There are reasons to believe that in the near future most of the calculators, online tools and projections will automatically be generated by Python coded applications. This is incredibly important because it states the fact that the current Machine Learning development level is at a point in which we are able to create and monitor complex finance matters.
With dozens of applications available, machine learning is definitely going to be the biggest focus in the near future, given the fact that automating certain sides of a business can definitely be a very impactful thing.
About the Author
Paul Matthews is a Manchester based business writer who writes in order to better inform business owners on how to run a successful business. You can usually find him at the local library or browsing Forbes’ latest pieces.
Related content from StrategyDriven