Course Content
derivatives and gradient
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DEMO : gradients – using excel – notebook
00:31
Gradient descent
00:00
build linear regression using gradient descent
00:00
types of gradient descent
00:00
DEMO : build linear regression using Stochastic Gradient Descent
00:00
Stochastic models in sklearn
In scikit-learn, stochastic models refer to a class of algorithms that involve randomness in their training process. These models are typically used for large-scale datasets when it is computationally expensive or infeasible to process the entire dataset at once. Instead, they perform updates on a subset of the data or use random sampling techniques.
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SGDClassifier
00:00
SGDRegressor
00:00
Mini-Batch K-Means
00:00
Machine Learning – Part 4 – Gradient Based Models (Pre-Cursor To Deep Learning)
About Lesson

This is a variant of the K-means clustering algorithm that performs updates on randomly selected subsets (mini-batches) of the data instead of the entire dataset. It is particularly useful when dealing with large datasets where the entire dataset cannot fit into memory. Scikit-learn provides the MiniBatchKMeans class for mini-batch K-means clustering.

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