Studentย โขย 2m
What is a Neural Network? Think of a neural network like your brain learning to recognize a dog. Imagine you're a child. At first, someone shows you a picture of a dog and says, โThis is a dog.โ Next time, they show you another animal and ask, โIs this a dog?โ You guess. If you're right, great! If not, they correct you. Slowly, you start to understand: Dogs have four legs. They bark. They have fur. This is how a neural network learns! Input layer = the features (legs, bark, fur) Hidden layers = the brain analyzing patterns Output = the answer: โYes, this is a dog.โ The more pictures (data) you see, the smarter you get โ just like a neural network! Used in: Face unlock, Google Translate, Self-driving cars, Netflix recommendations.
Building Snippetz la...ย โขย 5m
How AI Works 1. Neural Networks โ AIโs Brain AIโs neural networks consist of three layers: Input Layer: Takes in raw data (e.g., an image). Hidden Layers: Process data to find patterns (e.g., detecting edges, shapes). Output Layer: Produces the fi
See MoreJust go with the flo...ย โขย 3m
The secret to creating an error free AI is the main science behind ai is we give output and we have a expected output in between we have a fine layer in which we have neural network we need to increase the neural network in the layers instead of add
See MoreBe an entrepreneur, ...ย โขย 1m
A universal currency that completely replaces both physical and digital forms. Some ideas:- 1. Biometric/Physical Identity-Based Currency Idea: Each person's unique biological data (DNA, advanced fingerprint, retina/neural patterns) becomes their c
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Read this on internet today, A story that will change your way you think about marketing. There's a little boy he buys a dog and his dad says he has to take care of it. Boy agrees. One day the boy realizes that the dog has ticks and he gets really
See MoreGigaversity.inย โขย 1m
We developed a deep neural network for forecasting internal resource demand across systems, expecting it to outperform traditional models. But in deployment, a simple linear regression delivered better accuracy, stability, and faster inference times.
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