CHICAGO, May 24, 2023 (Globe Newswire) — global Automated Machine Learning (AutoML) Market Its size is expected to grow from US$ 1 billion in 2023 to US$ 6.4 billion by 2028, at a CAGR of 44.6% during the forecast period. According to a new report from MarketsandMarkets™. No-code and low-code platforms have revolutionized the way companies approach machine learning. This allows users with little or no programming experience to build and deploy machine learning models quickly and easily. No-code and low-code platforms, AutoML tools provide a streamlined approach to automating and optimizing the model building process.
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Report scope
| Reporting metrics | detail |
| Market size available over several years | 2017-2028 |
| Base year considered | 2023 |
| Forecast period | 2023-2028 |
| Forecast unit | Value (USD million/USD billion) |
| Target segment | Offerings, Applications, Industries, Regions |
| Target area | North America, Europe, Asia Pacific, Middle East and Africa, Latin America |
| Target company | IBM (US), Oracle (US), Microsoft (US), ServiceNow (US), Google (US), Baidu (China), AWS (US), Alteryx (US), Salesforce (US), Altair (US), Teradata (US), H2O.ai (US), DataRobot (US), BigML (US), Databricks (US), Dataiku (France), Alibaba Cloud (China), Appier (Taiwan), Squark (US), Aible ( Datafold (US), Boost.ai (Norway), Tazi.ai (US), Akkio (US), Valohai (Finland), dotData (US), Qlik (US), Mathworks (US), HPE (US)), Spark Cognition (USA). |
The automated machine learning market is segmented into solutions and services based on their offerings. The solutions segment is expected to grow at a higher compound annual growth rate (CAGR) during the forecast period. The solution segment is divided based on type and deployment. This department studies platforms and software applications by type. By deployment, it is further divided into cloud and on-premises. AutoML solutions are designed to automate many of the tasks associated with developing and deploying machine learning models, allowing organizations to harness the power of machine learning without the need for advanced data science or machine learning expertise. It becomes easy to use. AutoML solutions are becoming an increasingly important tool for organizations looking to harness the power of machine learning to gain insights from their data and make better decisions.
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Based on application, the market is classified into data processing, feature engineering, model selection, hyperparameter optimization and tuning, model assembly, and other applications (metric selection, monitoring and problem checking, outcome analysis). increase. These capabilities allow users to create accurate and reliable models without requiring extensive knowledge of machine learning algorithms and are critical to the success of AutoML platforms. Offering these capabilities, his AutoML platform enables domain experts to build machine learning applications without deep knowledge of statistics and machine learning, thus increasing the speed and efficiency of model creation.
Based on verticals, the automated machine learning market includes BFSI, Retail & E-Commerce, Telecommunications, Manufacturing, Healthcare & Life Sciences, IT/ITeS, Automotive, Transportation & Logistics, Government & Defense, Media & Entertainment, and Others. vertical sectors (Education, Transportation, Logistics). Many businesses are rapidly leveraging machine learning and artificial intelligence (AI). Investment banking is increasingly moving to replace human labor with this new technology, especially when it comes to processing and assimilating large amounts of data. For example, several investment banks have replaced entry-level financial analysts with automated systems to analyze financial data and draw insightful conclusions. Data validation and ensuring that data sources from various systems are in sync is done using AI bots. The vertical growth of the healthcare and life sciences industry is expected to grow at the highest CAGR during the forecast period.
The automated machine learning market is segmented into five regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America. The presence of various players and increasing adoption of AI and ML technologies by companies are some of the key factors driving the growth of his AutoML market in North America. Europe has seen steady adoption of AutoML solutions and services within the market. Europe is expected to rank second in terms of market size and share during the forecast period. Growing demand for AutoML solutions that can automate machine learning processes and make them more accessible to enterprises is driving the growth of the European market. Asia Pacific is expected to register the highest growth rate during the forecast period. The AutoML market is expected to witness significant development and adoption of its solutions across the Asia-Pacific region during the forecast period. Rising investment in IT infrastructure and rapid adoption of emerging technologies across several verticals are expected to drive the AutoML market.
Frequently Asked Questions (FAQ)
What is Automated Machine Learning?
Automated machine learning (AutoML) is the process of automating many of the tasks involved in building machine learning models. Apply algorithms to handle tasks such as feature engineering, hyperparameter tuning, and model selection, making them more user-friendly and efficient. AutoML is a valuable tool for businesses and individuals looking to harness the benefits of machine learning without requiring extensive knowledge or expertise.
What are the key factors underpinning the market growth of automated machine learning?
Key factors supporting the market growth of automated machine learning include increasing demand for improved customer satisfaction and personalized product recommendations with AutoML, growing need for accurate fraud detection, increasing data volume and complexity, This includes the growing need for business transformation through intelligent automation using AutoML.
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