What is Neural network?Neural network kya hai?

🧸 Think of it likeAise samjho

Like a big team passing notes: each member adds a little judgement, and together they reach an answer. Practice tunes how much they trust each other's notes.Ek badi team jaisa jo notes aage badhaati hai: har member thoda faisla jodta hai, aur milkar jawaab tak pahunchte hain. Practice se tay hota hai kaun kiske notes pe kitna bharosa kare.

📘 ExplainedVistaar se

Each neuron takes a weighted sum of inputs and applies an activation function; layers stack these to learn complex patterns. Networks are trained with backpropagation and gradient descent. Variants include convolutional networks for images and transformers for language.Har neuron inputs ka weighted sum leta hai aur activation function lagata hai; layers inhe jod kar complex patterns seekhti hain. Networks backpropagation aur gradient descent se train hote hain. Variants: images ke liye convolutional networks aur bhasha ke liye transformers.

💡 Real exampleAsli example

A network that takes pixel values and outputs 'cat' or 'dog'.Network jo pixel values leta hai aur 'cat' ya 'dog' deta hai.

📖 Learn it step by stepStep by step seekho

• Neural networks: layers that learnNeural networks: layers jo seekhti hain

🔗 Related termsJude hue shabd

• Deep learningMachine learning with neural networks of many layers, great for images, speech and text.Kai layers wale neural networks ke saath machine learning, images, awaaz aur text ke liye badhiya.
• Activation functionA small maths function inside each neuron that lets neural networks learn curves, not just straight lines.Har neuron ke andar ek chhota maths function jisse neural networks sirf seedhi lines nahi, curves bhi seekh paate hain.
• BackpropagationThe method neural networks use to work out how much each weight contributed to the error, so it can be adjusted.Woh tarika jisse neural network pata lagata hai har weight ne error mein kitna yogdaan diya, taaki use badla ja sake.