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Introduction to Optimization for Machine Learning [Lecture 22]
Understanding Optimization in Machine Learning: The Key to Smarter Models Ever wondered what makes machine learning models "learn"? At the core of it all lies optimization, the process of fine-tuning a model to ensure it performs its task accurately—be it predicting outcomes, classifying data, or finding patterns. The journey of optimization ...
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Insightforge | Data Science & AI on Instagram: "Gradient Descent is an optimization technique used to train machine learning models — it helps find the best set of parameters (like weights in a neural network) that minimize the loss function. Imagine the loss function as a hilly surface every point represents a different combination of parameters. Our goal? To move downhill toward the lowest point (minimum loss). To know which way to move, we calculate the gradient, which shows how the loss chan
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