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What is Data stewardship?

Data stewardship is the practice of managing, securing, and maintaining data integrity throughout its lifecycle. It involves overseeing data governance, quality control, compliance, and ethical usage, ensuring that data remains accurate, accessible, and aligned with business or regulatory requirements.

Layer (deep learning)
A layer in deep learning is a fundamental building block of neural networks, where computations such as feature extraction and pattern recognition occur. Deep learning models consist of multiple layers, including input, hidden, and output layers, which enable AI systems to learn complex relationships in data for tasks like image recognition and NLP.
Reinforcement Learning
Reinforcement learning refers to a type of machine learning where an agent learns optimal behaviors by interacting with an environment through rewards and penalties. It is widely used in robotics, gaming, finance, and autonomous systems.
Upsampling
Upsampling refers to increasing the resolution or quality of data, particularly in image processing and machine learning. It enhances model accuracy in tasks like super-resolution and data augmentation.

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