Top Machine Learning Trends to Look For in 2020

The recent growth of data explosion around the world has led to the acceleration of Machine Learning, which leverages data analysis methods to give computer systems the ability to learn. The growth of the technology is rapidly increasing largely because it helps companies to assess troves of data to find out patterns quickly than humans. Most businesses across diverse industries are unleashing the power of machine learning and integrating it exponentially as a core technology.

Considering industry analysis, the market of machine learning is predicted to reach from US$1.03 billion in 2016 to US$8.81 billion by 2022, growing at a CAGR of 44.1 percent during the projected timeframe.

Here are some top Machine Learning Trends everyone should look for in 2020.

Improved Cybersecurity

Machine Learning has the potential to enable cybersecurity systems to evaluate patterns and learn from them to assist in warding off potential attacks and responding to changing behavior. With the help of this tech, cybersecurity teams will get access to thwart threats and retort to potential attacks in real-time effectively. Machine Learning-driven applications have unfolded from email spam and malware filtering to envisioning and recommending actions. This year, forward-looking companies will see significant advantages from the technology’s real-time financial applications, including anomaly detection, self-auditing systems and previous transaction-based suggestions.

Augmentation of Voice Tech

Voice technology has been around for several years, invading people’s daily lives through built-in speech recognition in smartphones, game consoles and smartwatches. The technology is nothing new as it has come a long way since tech giant IBM introduced its first speech recognition machine in 1962. However, as technology advances rapidly, voice tech has increasingly made its entrance into modern lives with the introduction of voice-enabled applications such as Alexa, Siri, Cortana, among others. Each of the new voice-assistant devices people use rely on AI and machine learning. However, as research and development in this space will likely upsurge, it is expected that the increase in voice technology is evident in 2020 and beyond.

Recommendation System

Today, customers are expecting more personalized products and services while engaging with a brand. However, this creates opportunities for businesses to explore a more advanced approach that can help retain their customers efficiently. By leveraging machine learning techniques and disparate data regarding both products and users, companies can be able to create a product recommender system to generate and deliver suggestions for items or content an individual user would like to purchase or engage with. Simply, it creates a personalized offering using a customer’s previous information. This process dramatically enhances user-product and user-brand relationships eventually.

Digital Data

In today’s business landscape, data is the new fuel, enabling companies to make effective data-driven decisions to stand out in crowds. In the present time, the world is extensively producing data regularly using connected and smart IoT devices. Processing these huge amounts of data is very complex, even for conventional software systems. In this case, making use of Machine Learning to thoroughly comprehend the scenarios and classify the superfluous data so it can be deleted or rather forgotten and will only process data that can be useful for businesses. Machine Learning algorithms are effective in data collection, analysis, and integration, enabling big data operation through Data Labeling and Segmentation, Data Analytics, and Scenario Simulation.