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Deep Learning for Computer Vision: Building Convolutional Neural Networks from Scratch
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Deep Learning for Computer Vision: Building Convolutional Neural Networks from Scratch

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MIT · Hands-On Deep Learning Spring 2024 · LECTURE 3

Rama Ramakrishnan teaches this session of MIT's 15.773 Hands-On Deep Learning course, recapping the standard neural network training flow before walking through building a convolutional neural network step by step in Colab. The class works through the practical mechanics of setting up a deep learning pipeline for computer vision, from data handling to model construction, with an emphasis on hands-on coding rather than abstract theory. Ramakrishnan narrates each step as it appears on screen, making the session useful as a followed-along coding session as much as a lecture. Part of a Spring 2024 MIT OpenCourseWare series aimed at giving students working familiarity with deep learning tools through direct implementation rather than lecture-only instruction.

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Lecture facts

Runtime compared with the other 350 Mathematics lectures
Runtime1 h 17 m
Compared with MathematicsLonger than 60%
This series

Hands-On Deep Learning Spring 2024

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Lecture 3 of 112 h 15 m before this · 13 h 46 m in total

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