News Market Insights

The global AutoML market attained a value of $269.6 million in 2019 and is predicted to generate a revenue of $14,511.9 million by 2030. Furthermore, the market is predicted to progress at a CAGR of 43.7% between 2020 and 2030. The rising requirement for efficient fraud detection technologies, the growing demand for personalized product recommendations, and the increasing necessity of predictive lead scoring are the major factors driving the progress of the market. The increasing prevalence of fraudulent incidents is making the prevention and detection of frauds a huge challenge for companies operating in different industries. Currently, various organizations are using conventional machine learning techniques and big data for detecting and preventing frauds.  However, this dataset can be very imbalanced and extremely skewed in terms of both negative and positive classes. Therefore, in order to get precise and accurate results, automated machine learning solutions are increasingly ...

The rising prevalence of fraudulent incidents is a major factor fuelling the progress of the automated machine learning market all over the globe. Many companies are increasingly adopting advanced technologies and solutions such as conventional machine learning techniques and big data for detecting and preventing frauds. However, because of the high generation of data and high imbalance and skewed nature of the datasets, in terms of negative and positive classes, organizations are incorporating AutoML solutions for data preprocessing, evaluation, missing data management, data analysis, and various other processes. The major reasons behind the growth of the automated machine learning (autoML) market are the rising demand for advanced fraud detection solutions and personalized recommendations on various products and increasing awareness about predictive lead scoring. Due to these reasons, the market size is expected to increase from $269.6 million in 2019 to $14,511.9 million by 2030, at...