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5 Innovative Machine Learning Trends in 2020


Machine Learning is on track to be worth around USD 9 billion by 2023. This is due to the fact that the ML industry is booming at a rapid rate. The impact of such technology goes beyond the internet industry. They will reach the agriculture, legal, automobile, and health industries. People are more concerned and interested in knowing how the integration of ML can benefit their business. 

To remain relevant and at the forefront of fast-paced and rapidly changing verticals, innovation is necessary. As such, it is significant to keep track of new progress in science and technology.

Let’s examine the machine learning trends of 2020:

1. Cloud Computing Optimization 

The cloud computing industry is projected to increase to over $220 billion in 2020 from $175.8 billion in 2018. The increasing demand for cloud services will attract the provider to utilize artificial intelligence. At present, new customers require certified specialists to use cloud platforms that make cloud computing solution adoption expensive. In 2020, service providers will leverage AI and ML to disrupt this trend. Machine Learning will aid service providers in understanding customer requirements. ML systems will then improve the customer experience. Therefore, the deployment of cloud-based apps for startups will be inexpensive.

2.     Data Lakes and Software as a Service (SaaS) for Business Analytics

As it becomes simpler to collect and store data, companies will see the rewards of adopting machine learning (ML). Data Lake storage is also gaining a grip in the tech world, and for a very good reason, it has the capability to pile up unstructured data until it is ready for use. Data Lakes often benefit from cloud storage, making data storage scalable and affordable.



However, when the data lake is tied to software as a service (SaaS) tools or platforms, the procedure becomes streamlined. Suddenly, those who are not the expert in AI and ML algorithms still have access to these capabilities. So, it is crucial for organizations to strategize the implementation process and examine how machine learning can benefit their business.

3.     The Massive Collaboration of Technology

Companies have found that there are increased benefits gained from pairing modern technologies. As such, the use of machine learning, as well as artificial intelligence, will also lead to the adoption of other cutting-edge technology. For instance, machine learning and predictive analytics, when used in tandem, lead to powerful predictions to inform business decisions. Machine learning and artificial intelligence can also prepare data for predictive analytics and data visualization. 

Machine learning also accelerates the improvement of natural language processing (NLP) which explains how computer programs understand human language. Benefits count sentiment analysis and classification, improved text analytics, among others. Because of this automated learning, advancement can occur at a rapid rate than what would occur generally. 

4.     Improve Cyber Security by Discovering Cyber Attacks

Each day, around 230,000 malware samples are generated by hackers stated Panda Security (THE well-known Spanish company). ML solution makes it trouble-free to interact with clients. Machine learning can provide an automated response to specific cyber-attacks requiring no human intervention. Its advanced cyber defense program benefits the inter-connected tech world and saves them from extortion challenges. 

5.     Rapid Acceptance of ML Will Drive Growth

There is growing concern that machine learning could replace the workers. However, the fact is such demand will increase the jobs in data science. There is also a growing space for those who are interested in developing business intelligence tools. As the adoption of machine learning and artificial intelligence continues, enterprises will look for specialists to find out where they should direct their resources and efforts. While the job scenario may shift, there is a promising future of candidate collaborating machine learning technology to increase accuracy and productivity.


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