Free course on learning deep learning concepts
A conceptual and architectural journey through computer vision models in #deeplearning, tracing the evolution from LeNet and AlexNet to ResNet, EfficientNet, and Vision Transformers.
The #course explains the design principles behind skip connections, bottleneck blocks, identity preservation, depth/width trade-offs, and attention.
Each chapter combines clear illustrations, historical context, and side-by-side comparisons to show why architectures look the way they do and how they process information.
Grab it on YouTube
https://youtu.be/tfpGS_doPvY?si=1L_NvEm3Lwpj_Jgl
👉 @codeprogrammer
A conceptual and architectural journey through computer vision models in #deeplearning, tracing the evolution from LeNet and AlexNet to ResNet, EfficientNet, and Vision Transformers.
The #course explains the design principles behind skip connections, bottleneck blocks, identity preservation, depth/width trade-offs, and attention.
Each chapter combines clear illustrations, historical context, and side-by-side comparisons to show why architectures look the way they do and how they process information.
Grab it on YouTube
https://youtu.be/tfpGS_doPvY?si=1L_NvEm3Lwpj_Jgl
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