· ai
Neural Networks: Zero to Hero
Article URL: https://karpathy.ai/zero-to-hero.html Comments URL: https://news.ycombinator.com/item?id=46485090 Points: 32 Comments: 1...
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- · software
MyTorch – Minimalist autograd in 450 lines of Python
Article URL: https://github.com/obround/mytorch Comments URL: https://news.ycombinator.com/item?id=46483776 Points: 25 Comments: 1...
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ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth
Overview ZoeDepth predicts depth from a single image, handling both near and far objects accurately. It combines two learning strategies: one that preserves me...
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Adversarial Attacks and Defences: A Survey
Overview Today many apps use deep learning to perform complex tasks quickly, from image analysis to voice recognition. However, tiny, almost invisible changes...
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Mish: A Self Regularized Non-Monotonic Activation Function
Overview Mish is a simple activation function that can noticeably improve the performance of image‑based AI models. By replacing the standard activation with M...
- · ai
Computer Vision Services: Building Intelligent Visual Systems with Oodles
Images and videos contain massive amounts of data—but extracting meaningful insights from them requires advanced AI systems. Computer Vision Serviceshttps://www...
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Part 7: CUDA Integration with Python
XOR Test After successfully setting up the Neural Network, I tested it with the XOR operation. XOR is a non‑linear operation, so it’s kind of a “Hello World” f...
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When Neural Networks Stop Learning: Understanding Vanishing Gradients
What is the Vanishing Gradient Problem? In neural networks, the gradient tells the network how much to change each weight to reduce the error. If the gradient...
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Understanding Gradients: The Engine Behind Neural Network Learning
In the previous article, we explored activation functions and visualized them using Python. Now, let’s see what gradients are. What Is a Gradient? Neural networ...
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AutoAugment: Learning Augmentation Policies from Data
Overview AutoAugment is a method that automatically discovers effective image augmentation policies. By systematically testing many simple transformations—such...
- · ai
Vectorization in Neural Networks: A Beginner’s Guide
Artificial intelligence may sound complex, but at its core it’s all about numbers. Neural networks—the engines behind modern AI—can’t work directly with raw tex...
- · ai
Activation Functions: How Simple Curves Power Neural Networks
Activation Functions – The Building Blocks of Neural Networks In my previous article we touched upon the sequence‑to‑sequence modelhttps://dev.to/rijultp/seque...