Machine Learning & Business: 4 Upcoming Trends That Will Benefit You in 2020

While the general idea of the internet was created in the 1960s, the internet that we know today, came into existence with Tim Berners-Lee in the 1990s. Since then, the internet has only accelerated in its growth and use, giving billions of individuals access to more than 50 Zettabytes of data. Do you know how large 1 zettabyte is? To help, we will convert this into a more familiar term, gigabyte. 1 zettabyte is equal to 9313225746715.48 gigabytes. That’s a lot! This amount of data has given way to almost 2 billion websites of which 400 million are active, 4.5 billion active internet users, across 22 billion connected devices. So, how can businesses benefit from this amount of data in a quick and efficient manner and what will that look like in 2020? Through a subset of artificial intelligence called machine learning.

What Exactly Is Machine Learning & Why Are Businesses Looking to Implement It

Many businesses are choosing to explore how to implement machine learning services, which is a subset of artificial intelligence, because it gives businesses a way to analyze and learn from data through an autonomous method. Here is how it works.

Machine learning is the process used to teach a computer system how to make accurate predictions based on data that is fed to it. A computer system will use algorithms that can learn from the data without relying on any rule-based programming. This type of system is already in use today and is probably something you’ve interacted with, without even realizing it. For instance, Netflix uses machine learning to recommend content to you, Instagram uses it to determine which newsfeed posts you will see, and Duolingo uses it to power its language learning application.

How Does a Machine Learn, Exactly?

Through the use of associations. The machine’s algorithms are categorized into 5 different learning subsets that provide associations, classifications, and different types of learning.

• Associations is when the computer system finds a link between two actions and can therefore assign a probability based on how frequently this probability or action will occur.
• Classifications are used by machine learning systems to deploy models that make predictions based on previously analyzed datasets.
• Supervised learning in a machine learning system will use models that provide correct output data based through a set of rules and input data. The rule used is determined by a human individual who builds the model.
• Unsupervised learning removes the human element and allows the algorithm model to make associations without a rule basis to follow.
• Reinforcement learning uses sequential actions to achieve a goal. A reward and possible actions are defined, and a model is used to run through scenarios that would achieve the desired outcome.

How Is Artificial Intelligence & Machine Learning Different From One Another?

It is likely that you’ve come across these two terms being used interchangeably, despite the fact that they have distinct differences to one another. The easiest way to define the difference between them is what their end goal is.
While artificial intelligence attempts to have computers mimic human intelligence, machine learning specifically focuses on building machines that can analyze data, learn from the data, and predict probabilities without human interference. To put it simply, artificial intelligence leads to intelligence and is used to increase the likelihood of finding an optimal solution, while machine learning, focuses on increasing the accuracy of analyzing and learning from data to develop new insights through an autonomous vehicle.

Why Should Businesses Care About Machine Learning Trends?

Machine learning services can help businesses use the huge amounts of data that they have collected in order to develop and gain insight into actionable predictions for fostering growth and finding investment opportunities and resources. Artificial intelligence can help companies increase their efficiency, boost sales, and improve customer relationships, while machine learning services, can take data from these categories, learn from it, and give businesses a pathway to more profit and better customer understanding. Here are 4 machine learning trends that businesses should watch out for in 2020.

• Data Entry Automation & Removal of Spreadsheets. The majority of businesses currently use manual data entry through spreadsheet programs to collect, manage, and store the information. With machine learning, data entry can become an automated process that eliminates human error, saves the business time, and gives them an edge against competitors.
• Product Upselling via Recommendations. Businesses that are in the e-Commerce space know how convenient and cost-effective it is for consumers to use their websites to make their shopping purchases. Machine learning can help these businesses upsell products by making recommendations based on consumer purchase history, behaviors, and other consumer patterns. Unsupervised learning can be used here to increase revenue with no extra effort.
• Predictive Maintenance & Efficiency. Using preventative and corrective maintenance procedures is necessary for manufacturing businesses. Machine learning can be used within this space to increase how efficient these preventative and corrective maintenance procedures are. For instance, machine learning will be able to predict through visual patterns, when a shipping container will need to be replaced or how to streamline project workflows on construction sites by expanding drone capabilities.
• Image Recognition. While image recognition has been around for decades, machine learning takes it to a new level and allows us to identify greater patterns for insight. This can be used in businesses that have security and surveillance routines, require object recognition, or need image recognition for land surveying.

The artificial intelligence market has already grown to be a multi-billion-dollar industry, but with the advancement of machine learning throughout 2020, businesses can now use it to become smarter with their data. This will help businesses boost efficiency, increase worker safety, and uncover insights into outcomes that may have never been on the table in the first place.