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Code a Neural Network in Python | Sunny vs Rainy Prediction | Hrworkoze
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AI • Machine Learning • Tech on Instagram: "In a feedforward neural network (also known as an MLP), neurons are arranged in layers where each neuron receives inputs from the previous layer, multiplies them by corresponding weights, adds a bias term, and applies an activation function to produce its output. This process continues layer by layer until the final output is produced. When an example is passed through the network, the output is compared to the target value, and the difference is calcu
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Insightforge | Data Science & AI on Instagram: "Neural networks: brains behind digit recognition A neural network is built from tiny computational units called neurons, which store numbers and activate based on inputs. Take the MNIST dataset — each 28×28 image of a handwritten digit provides 784 pixel values, with each pixel acting as an input neuron. The data flows forward: The first layer reads raw pixels. Deeper layers transform these values using weights + activation functions. The final lay
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Sujar • Tech | AI | Coding on Instagram: "Let’s build a Machine Learning Model to predict numbers using a Convolutional Neural Network If you want to try out my code make sure to comment “Number” and I’ll DM it to you. Instagram is a bit weird so make sure to follow before commenting since it sometimes doesn’t send unless you’re following #coding #computerscience #cs #softwareengineer #machinelearning #ai #programming"
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Code.hub on Instagram: "This is what a 3D visualization of a neural network looks like. Save & follow for more. . Dm for credit. . . #coding #programming #software #aritficialintelligence #ai #machinelearning #software #coder #softwarengineering #neuralnetwork #viral #animation #computer #cse #python #java #code"
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The AI Web on Instagram: "One of the key technologies behind this capability is the Convolutional Neural Network (CNN), a fundamental architecture in deep learning for computer vision. CNNs mimic the way our brains process visual input, making them highly effective at tasks like object detection and image classification. ➡️ Convolutional Layers act like scanning lenses, identifying patterns such as edges or textures in small image sections ➡️ Pooling Layers compress these feature maps to highlig
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AI • Machine Learning • Tech on Instagram: "A neural network “learns” by adjusting its parameters (weights and biases) by increasing or decreasing them numerically so that the network can make increasingly more accurate predictions. The output is compared to the actual target values using a loss function, which quantifies the prediction error. To minimize the error, the network performs backpropagation, an algorithm that computes the gradient (set of all partial derivatives) of the loss with res
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AI • Machine Learning • Tech on Instagram: "When a neural network learns, it’s like it’s drawing a line or boundary in space that separates different classes of data. For instance, we have data points with 3 different cities: Madrid, Paris, and Berlin. This boundary, in 3D space, acts as a plane that separates each class from each other. At first, the network might not have a very accurate boundary. But as the network learns from examples, it adjusts this boundary to better separate the classes
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