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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 | AI & Data Science on Instagram: "Stochastic Gradient Descent (SGD) is an optimization technique used to reduce a model’s loss and improve its performance. A good way to imagine it is like walking down a hill to reach the lowest point. The gradient tells you the slope and the direction to move downward. But instead of looking at the entire landscape (the full dataset), SGD looks at small random batches of data to estimate the slope at each step. Because it works with smaller sample
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