A machine learning stack bundles the software and tools needed to build, train, and deploy AI models. It typically includes data processing libraries, frameworks like TensorFlow or PyTorch, and deployment platforms. Data scientists and ML engineers use it to streamline workflows, while businesses leverage it to scale predictive analytics and automation, reducing time-to-market for intelligent applications.
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