The Europe Automated Machine Learning Market would witness market growth of 42.3% CAGR during the forecast period (2023-2029).
AutoML systems gather data from various internal (CRM databases) and external (social media & online data) sources about consumer behavior, firm size, and industry to analyze each lead and assign it a score. With the help of this score, one can tell if a lead is qualified for the business in the issue. In addition, the solution can provide reason codes for every lead, letting salespeople know the crucial aspects that make a lead worthwhile.
AutoML promises to make machine learning modeling accessible to people with little data science knowledge by streamlining and simplifying the process of developing and deploying machine learning models.
The difficult activities involved in machine learning include feature engineering, data preprocessing, hyperparameter tuning, model selection, and model deployment. By automating these processes, autoML systems enable users to construct machine learning models without considerable algorithmic or coding expertise. Because of several causes, the AutoML market has significantly expanded recently. First, there is a demand for streamlined and effective model-creation procedures due to the growing use of machine learning across various businesses. Businesses may use machine learning to their advantage using AutoML without hiring many data scientists.
Big data is used in the medical field to compute intricate statistics in large quantities and provide trends & patterns that are essential for applications in the healthcare sector. Big Data helps doctors identify potential issues before they arise. The use of Big Data by numerous companies has completely changed health care in Germany. These businesses work closely with health economists, statisticians, physicians, IT experts, and analysts to expand the body of information about optimal therapies that are based on evidence. Big Data in healthcare is responsible for managing this, and medical personnel can use it effectively with AI and ML. In light of this, the regional market is predicted to grow steadily in the upcoming years.
The Germany market dominated the Europe Automated Machine Learning Market by Country in 2022 and would continue to be a dominant market till 2029; thereby, achieving a market value of $587 million by 2029. The UK market is anticipated to grow at a CAGR of 41.1% during (2023 - 2029). Additionally, The France market would showcase a CAGR of 43.3% 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 Germany, UK, France, Russia, Spain, Italy, and Rest of Europe.
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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