The Growth Of Automated Machine Learning (AutoML)

One of the current trends in the data science industry is “Automated Machine Learning.” Most of the top-rated technology companies like Microsoft, Amazon, Google, and others have incorporated AutoML in their processes to enhance the effectiveness of their applications. It has changed the way organizations do business, and that’s why AutoML has been described as a “quiet revolution in AI.” By automating a major portion of the machine learning process, the solution has changed the data science landscape. All types and sizes of organizations have now started using AutoML to experience a significant rise in their productivity level. Automated Machine Learning has created a lot of buzz in the business sector, so before moving on to anything, first, let's discuss what automated machine learning is.

What is Automated Machine Learning?

Automated machine learning (AutoML) is an artificial intelligence-based solution that automates the process of applying machine learning to real-world problems. The solution helps in compensating for the shortage of data specialists in the data-driven industry as with the high degree of automation in machine learning, even the non-experts can efficiently use machine learning models.

The end-to-end application of automated machine learning facilitates the production of more straightforward solutions and the creation of models that usually outperform hand-designed models.

The growth of AutoML

AI and machine learning need the support of professional data scientists and engineers, which are currently in shortage in the industry. AutoML compensates for this need by automating the repetitive tasks of machine learning and at the same time boosting the productivity of the available data scientists. The solution has shortened the gap that was getting wider between the demand for data scientists and their availability. With the automation of repetitive tasks like selecting the data sources, data preparation & attribution selection, and marketing analytics, in addition to a few others, the data scientist can quickly move their focus on other essential tasks. The automated solution allows the data scientist to create more model versions in no time, enhance their quality and develop new algorithms. Here, we are writing down some benefits that data scientists received with the growth of AutoML:

• For citizen data researchers: AutoML has automated more than 40% of the data science tasks so that the data scientists can move their attention to core processes and make better use of their skills. The machine learning tools assist the data scientists in model creation by taking into consideration each and every aspect of different business applications like marketing analytics or client analytics.

• Automates the process of model building: AutoML selects the best model for the problem at hand. By automating the application of machine learning techniques to data, ML helps data scientist to save time and effort involved in pre-processing, determining features, and tuning models. The solution will help you find the best model by creating a large number of models and analyzing them as per your business requirements. The intelligence-based solution can also create improved versions of the current versions.

• Automates end-to-end business processes: In some instances, AutoML can automate an entire business process. Many organizations have combined automated machine learning with feature engineering to actively automate certain business processes. The solution also helps in breaking down the big data silos to provide relevant information about the business and the market it is working in. With the right information in hand, better business decisions can be made to ensure positive outcomes.

• Help organizations make the most out of machine learning: Large data sets can only be useful to a business if they are processed accurately. To derive better insights, each and every piece of data must be precisely collected, cleaned, improved, and made analysis-ready. AutoML is a process that helps all sizes and types of businesses to make the best use of machine learning. Your business data is an invaluable resource that can be efficiently handled with AutoML.

The future of AutoML

The data scientists have made predictions that in the coming time, AutoML will help businesses to handle most of the data cleaning process. The solution will get better day by day and assist the data-driven industry in managing its core processes efficiently and hassle-freely. Furthermore, it does not matter in which field you are doing business, AutoML is the methodology you will require to extract and handle your invaluable resources.