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.
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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 being used.
These solutions optimize processes such as data exploration, data reprocessing, missing data handling, feature engineering, training, evaluation, and model selection without requiring any human intervention. Besides this factor, the thriving healthcare industry is predicted to offer lucrative growth opportunities to the players operating in the automated machine learning market across the globe.
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This market research report provides a comprehensive overview of the market
- Future potential of the market through its forecast for the period 2020– 2030
- Major factors driving the market and their impact during the short, medium, and long terms
- Market restraints and their impact during the short, medium, and long terms
- Recent trends and evolving opportunities for the market participants
- Historical and the present size of the market segments and understand their comparative future potential
- Potential of on-demand logistics services, so the market players make informed decisions on the sales of their offerings