Convolution
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What is Convolution?
Convolution is a mathematical operation that involves sliding a filter (also known as a kernel) over an input image or feature map. At each location, the filter performs element-wise multiplication with the corresponding part of the input, and then sums the results. This sum becomes a single value in the output feature map. By sliding the filter across the entire input, the convolution operation extracts features and patterns present in the image, such as edges, textures, or shapes.
Free resources to learn Convolution
More in stage 31: Convolutional Neural Network
Convolution: common questions
Can I learn Convolution in Hindi?
This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain Convolution in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.
Is this Convolution tutorial for beginners?
It is lesson 116 of 150 in the free Machine Learning roadmap, in stage 31, Convolutional Neural Network. If you are new to Machine Learning, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.