A free MIT guide to key computer vision concepts 📘

Link: https://visionbook.mit.edu/ 🔗

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500 AI/ML/Computer Vision/NLP projects with code 🚀

This is a large collection of 500 ready-made projects in the field of machine learning, deep learning, computer vision, and NLP 🧠

All examples come with code, so you can not just read them, but immediately analyze and run them ⚙️

➡️ Link to GitHub:
https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

#AI #MachineLearning #DeepLearning #ComputerVision #NLP #DataScience

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Diving deep into Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP. 🤖🧠

Lectures: 🎓📚
https://github.com/kmario23/deep-learning-drizzle

#DeepLearning #MachineLearning #AI #ReinforcementLearning #ComputerVision #NLP

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Most people memorize CNN equations without truly understanding what the convolution operation is actually doing.

Here's what happens during a CNN forward pass in under 60 seconds:

🔹 Kernel (Filter) Setup:
A 3 × 3 kernel (filter) slides across the input matrix.

🔹 Element-Wise Multiplication:
At each position, the kernel multiplies its weights with the overlapping input values and sums the results to produce a single scalar output (z₁, z₂, z₃, z₄).

🔹 Stride:
With a stride of 2, the kernel moves two steps horizontally and vertically, creating a compressed 2 × 2 feature map.

🔹 Flattening & Prediction:
The feature map is flattened into a 1D vector, which is then passed through the remaining network layers to generate the final prediction (ŷ). This prediction is used to compute the loss (L).

📌 Save this post so you can quickly review how CNNs perform convolution before your next Deep Learning or Computer Vision interview.

✈️ Share this reel with an AI engineer, student, or anyone learning Deep Learning who wants to visualize how CNNs actually work.

C: far1din

Credits to the original creator.
Shared for inspiration and educational purposes only.
If you are the copyright owner and prefer this content to be removed, please send a DM and it will be removed respectfully.

#ConvolutionalNeuralNetworks #DeepLearning #ComputerVision #MachineLearning #AIEducation

📚 "Fundamentals of Computer Vision" is a free online book published by MIT Press, providing a broad introduction to computer vision from the perspectives of image processing and machine learning.

🔍 It covers topics such as image formation, training and backpropagation, image filtering and Fourier analysis, CNNs, RNNs, and transformers, generative models, representation learning, 3D geometry, motion estimation, object recognition, models that work with images and text, and much more.

💡 I particularly appreciate that the entire book is available directly in HTML, with a clear and user-friendly layout, and numerous diagrams and visualizations that help to understand the concepts.

🔗 https://visionbook.mit.edu/

#ComputerVision #MachineLearning #AI #TechBooks #MITPress #Education

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