Stochastic Gradient Descent Explained with Python Code and Example
32:56
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Stochastic Gradient Descent Explained with Python Code and Example
Stochastic Gradient Descent Explained with Python Code and Example Stochastic Gradient Descent is a popular optimization algorithm used in machine learning for finding the optimal parameters of a model. In this video, we'll explain how Stochastic Gradient Descent works using a simple mathematical example, and show you how to implement it in ...
6.2K viewsMar 1, 2023
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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
1:18
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
Instagraminsightforge.ai
11K views5 months ago
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