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Global Automated Machine Learning Market Size study & Forecast, by Solution, by Automation Type, by End Users and Regional Analysis, 2023-2030
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Global Automated Machine Learning Market is valued at approximately USD 0.87 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 43.90% during the forecast period 2023-2030. Automated Machine Learning refers to the process of automating the end-to-end process of applying machine learning to real-world problems. The purpose of automated machine learning is to make machine learning more accessible to non-experts and streamline the workflow for experienced practitioners. It involves automating various steps in the machine learning pipeline, including data preprocessing, feature engineering, model selection, hyperparameter tuning, and model deployment. The Automated Machine Learning Market is expanding because of factors such as the growing volume of data and rising demand for machine-learning-powered chatbots. As a result, the demand for Automated Machine Learning has progressively increased in the international market during the forecast period 2023-2030.

Large datasets frequently include more complicated connections and patterns, and automated machine learning is getting access to large amounts of data, and can handle and record complex data structures, resulting in more sophisticated and accurate models. According to Statista, in 2020, the global volume of data accounts for 64.2 zettabytes and is projected to reach up to 181 zettabytes by the year 2025. Another important factor that drives the Automated Machine Learning Market is the increasing demand for the machine-learning-powered chatbot. Machine-learning-powered chatbots often require the deployment of models that can understand and generate human-like responses. Automated Machine Learning tools facilitate rapid model development and deployment, allowing organizations to quickly implement chatbot solutions without the need for extensive manual model tuning. In addition, as per Statista, the global chatbot market is projected to reach up to USD 1.25 billion by the year 2025. Moreover, the rising trend of cloud-based machine learning models and government initiatives towards the adoption of fraud detection technology is anticipated to create a lucrative growth opportunity for the market over the forecast period. However, the lack of standardization and rising threat to data privacy is going to impede overall market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Automated Machine Learning Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the increasing demand for artificial intelligence solutions in the region. The growing demand for quick turnaround times in deploying AI applications is addressed by AutoML. Automated processes speed up model development, allowing organizations to bring AI solutions to the market faster. This agility is crucial in industries where timely implementation of AI can provide a competitive advantage. The region's dominant performance is anticipated to propel the overall demand for Automated Machine Learning. Furthermore, Asia Pacific is expected to grow fastest over the forecast period, owing to factors such as supportive government initiatives towards the expansion of artificial intelligence in the region.

Major market player included in this report are:

Recent Developments in the Market:

Global Automated Machine Learning Market Report Scope:

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Solution

By Automation Type

By End Users

By Region:

Table of Contents

Chapter 1.Executive Summary

Chapter 2.Global Automated Machine Learning Market Definition and Scope

Chapter 3.Global Automated Machine Learning Market Dynamics

Chapter 4.Global Automated Machine Learning Market Industry Analysis

Chapter 5.Global Automated Machine Learning Market, by Solution

Chapter 6.Global Automated Machine Learning Market, by Automation Type

Chapter 7.Global Automated Machine Learning Market, by End Users

Chapter 8.Global Automated Machine Learning Market, Regional Analysis

Chapter 9.Competitive Intelligence

Chapter 10.Research Process

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