5 Neural Networks: MLP,CNN, RNN, Auto Encoder, GAN

Neural Networks are machine learning models inspired by the human brain. They act as digital clone of human brain due to their structure of interconnected nodes (neurons) and combination of multiple layers (input layer, Hidden layers and output layers) to process data, identify patterns and predict outcomes. Unlike traditional programming that follows strict if/else pattern(e.g., if condition is true, output 1; else output 0), a neural network analyzes raw data and predicts future outcomes based on learned patterns, rather than depending totally on hard-coded conditions. Types of Neural Network Neural Networks are loosely modeled after human brain however this is true for just some extent. Yes, they work similarly! For example, in an autonomous vehicle, they take input from sensors (like a human seeing an obstacle), process the data in hidden layers (like the brain thinking), and give an output action, such as reducing the car's speed (human reflex). However, they are not all the same