The Latin America, Middle East and Africa Automated Machine Learning Market would witness market growth of 50.2% CAGR during the forecast period (2023-2029).
Numerous businesses have actively automated some business operations by fusing automated machine learning with feature engineering. In order to give pertinent information about the company and the industry it serves, the solution also aids in dismantling massive data silos. As a result, making better business decisions can assure successful outcomes with the correct knowledge at hand. The best possible use of machine learning is facilitated for businesses. Only if they are handled accurately can large data sets be relevant to a business. Every piece of data needs to be meticulously collected, cleansed, upgraded, and made analysis-ready to yield superior insights.
By using AutoML, organizations of all shapes and sizes may utilize machine learning to its fullest potential. According to data scientists' projections, organizations will be able to manage the majority of the data-cleaning process with the help of AutoML in the future. With each passing day, the solution will improve and help the data-driven sector manage its essential operations smoothly and effectively. Furthermore, regardless of the industry the business operates in, AutoML is the methodology that is required to extract and manage priceless resources.
The oil-rich Gulf States are aggressively working to diversify their economies throughout the Middle East and Africa by utilizing artificial intelligence and machine learning. The majority of Gulf nations, constantly seeking to develop new technologies, have acknowledged the significance of modern technology. The United Arab Emirates leads the Arab region regarding technical innovation and acceptance. Additionally, initiatives related to smart cities and autonomous mobility are what is driving demand for AI and ML expertise in the region. Brazil and Uruguay are two Latin American nations implementing new programs and regulations to promote the adoption of sophisticated technologies in the region.
The Brazil market dominated the LAMEA Automated Machine Learning Market by Country in 2022 and would continue to be a dominant market till 2029; thereby, achieving a market value of $183.5 million by 2029. The Argentina market is experiencing a CAGR of 51% during (2023 - 2029). Additionally, The UAE market would witness a CAGR of 49.8% during (2023 - 2029).
Based on Application, the market is segmented into Data Processing, Feature Engineering, Model Selection, Hyperparameter Optimization & Tuning, Model Ensembling and Others. Based on Offering, the market is segmented into Solution and Services. Based on Solution Type, the market is segmented into Platform and Software Based on Solution Deployment, the market is segmented into Cloud and On-premise. Based on Vertical, the market is segmented into BFSI, IT & Telecom, Retail & Ecommerce, Media & Entertainment, Healthcare & Life Sciences, Government & Defense, Manufacturing, Automotive, Transportations, & Logistics, and Others. Based on countries, the market is segmented into Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria, and Rest of LAMEA.
Free Valuable Insights: The Worldwide Automated Machine Learning Market is Projected to reach USD 9.1 Billion by 2029, at a CAGR of 42.9%
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Oracle Corporation, IBM Corporation, Microsoft Corporation, Google LLC (Alphabet Inc.), Amazon Web Services, Inc. (Amazon.com, Inc.), Salesforce, Inc., Hewlett-Packard enterprise Company, Teradata Corporation, Alibaba Cloud (Alibaba Group Holding Limited) and Databricks, Inc.
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