Machine learning is a branch of artificial intelligence that enables computers to learn from data and

make predictions or decisions without being explicitly programmed. Machine learning can be used to

forecast market trends by analyzing historical and current data, identifying patterns and

relationships, and generating models that can extrapolate future outcomes. Machine learning can

also adapt to changing data and environments, and improve its accuracy and performance over

time1.

The other options are not commonly used to forecast market trends:

Serverless computing: This is a type of cloud computing that allows customers to run applications or

functions without managing or provisioning servers. Serverless computing can reduce the

operational and infrastructure costs, and improve the scalability and availability of the applications

or functions. However, serverless computing is not directly related to forecasting market trends,

although it can be used to deploy or run machine learning models or applications2.

Data warehouse: This is a centralized repository that stores structured and historical data from

various sources, such as databases, applications, or files. Data warehouse can support business

intelligence and analytics, and provide consistent and reliable data for reporting and decision

making. However, data warehouse is not a forecasting method, but rather a data storage and

integration system, that can be used as an input for machine learning or other forecasting methods3.

Accelerated computing: This is a type of computing that uses specialized hardware, such as graphics

processing units (GPUs) or field-programmable gate arrays (FPGAs), to accelerate the performance of

certain applications or tasks, such as machine learning, gaming, or video processing. Accelerated

computing can enhance the speed and efficiency of the applications or tasks, and reduce the power

consumption and costs. However, accelerated computing is not a forecasting method, but rather a

computing platform, that can be used to support or enable machine learning or other forecasting

methods4.

Reference:

Machine Learning for Forecasting Market Trends

Serverless Computing for Machine Learning

Data Warehouse for Business Intelligence and Analytics

Accelerated Computing for Machine Learning