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billion by 2031 at a CAGR of 34.20%. These base learners may vary in complexity, ranging from simple decisiontrees to complex neural networks. decisiontrees) is trained on each subset. Examples Random Forest, which builds an ensemble of decisiontrees. Naturallanguageprocessing tasks.
billion by 2031 at a CAGR of 34.20%. Naturallanguageprocessing ( NLP ) allows machines to understand, interpret, and generate human language, which powers applications like chatbots and voice assistants. Decisiontrees are easy to interpret but prone to overfitting. For a regression problem (e.g.,
Bureau of Labor Statistics predicts that employment for Data Scientists will grow by 36% from 2021 to 2031 , making it one of the fastest-growing professions. These statistics underscore the significant impact that Data Science and AI are having on our future, reshaping how we analyse data, make decisions, and interact with technology.
Meanwhile, the ML market , valued at $48 billion in 2023, is expected to hit $505 billion by 2031. Virtual Assistants : AI-driven assistants like Siri and Alexa help users manage daily tasks using naturallanguageprocessing. From virtual assistants to healthcare diagnostics, AI’s impact is growing rapidly.
billion by 2031, growing at a CAGR of 34.20%. DecisionTrees These trees split data into branches based on feature values, providing clear decision rules. These networks can learn from large volumes of data and are particularly effective in handling tasks such as image recognition and naturallanguageprocessing.
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