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`@@ -18,3 +18,16 @@ CNNs are widely used in various fields such as:`
`18`	`18`	`* Image Recognition: Identifying objects in images (e.g., facial recognition).`
`19`	`19`	`* Medical Image Analysis: Analyzing X-rays or MRIs for diagnostic purposes.`
`20`	`20`	`* Autonomous Vehicles: Object detection and scene understanding.`
	`21`	`+`
	`22`	`+RNN`
	`23`	`+==========`
	`24`	`+* RNN are a class of nerual networks that are excellent at processing sequential data`
	`25`	+* They maintain an internal state at time step `t` for input `x(t)`, and combines it with hidden state from the previous step `h(t-1)` to produce a new hidden state `h(t)`
	`26`	`+* h (t) = f [ W(h) * h(t−1) + W(x) * x(t) + b], W(h) and W(x) are weight matrics and b is the bias term, f is the activation function`
	`27`	`+`
	`28`	`+Applications:`
	`29`	`+==========`
	`30`	`+RNNs are commonly used in:`
	`31`	`+* Natural Language Processing: Tasks such as language modeling, text generation, and sentiment analysis.`
	`32`	`+* Speech Recognition: Processing audio signals to convert speech into text.`
	`33`	`+* Time Series Prediction: Forecasting stock prices or weather conditions based on historical data.`

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