Definition:
Machine learning is a branch of artificial intelligence that involves the use of algorithms and statistical models to enable computer systems to learn from data and improve their performance on a task. It has a wide range of applications, including image and speech recognition, natural language processing, and predictive analytics. The Machine Learning market includes software platforms, tools, and services that enable organizations to develop and deploy machine learning applications.
Additional Information:
The Machine Learning market comprises two key performance indicators: market sizes, and market sizes by industry. Market sizes are generated by the funding amount of Artificial Intelligence (AI) companies. Key players of the market include companies such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure.
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Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Mar 2024
Source: Statista Market Insights
Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Mar 2024
Source: Statista Market Insights
The Machine Learning market in Southern Asia, within the larger Artificial Intelligence market, is experiencing extraordinary growth rate due to increasing adoption of digital technologies, rising awareness of its potential in the healthcare industry, and the convenience of online services.
Customer preferences: The adoption of machine learning technology in Southern Asia is driven by the region's growing demand for advanced data analytics solutions. As the population becomes more digitally savvy, there is a rising demand for personalized and efficient services, such as chatbots and virtual assistants. With the increasing availability of internet and mobile devices, consumers are also showing a preference for AI-powered recommendation engines and predictive algorithms, which cater to their evolving lifestyle needs and preferences.
Trends in the market: In Southern Asia, the Machine Learning Market within the Artificial Intelligence Market is experiencing a surge in demand for natural language processing (NLP) technologies, driven by the rapid growth of e-commerce and online services. This trend is expected to continue as companies seek to improve customer engagement and increase operational efficiency. Additionally, there is a growing emphasis on data privacy and security, leading to the adoption of advanced machine learning solutions for fraud detection and risk management. These developments have significant implications for industry stakeholders, as they strive to stay competitive in a rapidly evolving market landscape.
Local special circumstances: In Southern Asia, the Machine Learning Market within the Artificial Intelligence Market is heavily influenced by the region's large population and rapid technological advancements. Countries like India and China have a growing demand for AI-based solutions in various industries, such as healthcare and finance. Additionally, the region's diverse cultural landscape also plays a crucial role in shaping the market, with different countries having unique preferences and adoption rates for AI technologies. Additionally, regulatory frameworks and policies differ across countries, impacting the development and deployment of AI solutions in the region.
Underlying macroeconomic factors: The growth of the Machine Learning Market within the Artificial Intelligence Market is also influenced by macroeconomic factors such as technological advancements, government support, and investment in infrastructure. Countries with favorable policies and strong investment in AI technologies are experiencing faster market growth compared to regions with regulatory challenges and limited funding. Additionally, the increasing demand for automation and data-driven decision making in various industries is driving the adoption of machine learning solutions, further fueling market growth.
Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Mar 2024
Source: Statista Market Insights
Data coverage: The data encompasses B2B, B2G, and B2C enterprises. Figures are based on the funding values from different industries for the market.
Modeling approach / Market size:Market sizes are determined through a top-down approach with a bottom-up validation, building on a specific rationale for each market. As a basis for evaluating markets, we use annual financial reports, funding data, and third-party data. In addition, we use relevant key market indicators and data from country-specific associations such as GDP, number of internet users, number of secure internet servers, and internet penetration. This data helps us estimate the market size for each country individually.
Forecasts:In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function and exponential trend smoothing are well suited to forecast digital products and services due to the non-linear growth of technology adoption. The main drivers are the level of digitalization, the number of secure internet servers, and the revenue of the Public Cloud market.
Additional Notes: The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russian-Ukraine war are considered at a country-specific level. The market is updated twice a year. In some cases, the market is updated on an ad-hoc basis (e.g., when new, relevant data has been released or significant changes within the market have an impact on the projected development). Data from the Statista Consumer Insights Global survey is weighted for representativeness.
Notes: Based on data from IMF, World Bank, UN and Eurostat
Most recent update: Sep 2024
Source: Statista Market Insights