neural.echo on TikTok
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neural.echo on TikTok
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TikTokneural.echo
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Ritika Singh on Instagram: "🚀Week 2: Deep Learning & Neural Networks Concepts: • What are Neural Networks? Perceptrons, activation functions (ReLU, Sigmoid, Tanh). • Feedforward Neural Networks (FNNs). • Backpropagation algorithm (intuition and basic understanding). • Introduction to Convolutional Neural Networks (CNNs) for image data. • Introduction to Recurrent Neural Networks (RNNs) for sequential data. Resources: • Deep Learning: “Neural Networks and Deep Learning” by Andrew Ng (DeepLearnin
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Explainr AI on Instagram: "Backpropagation: The Algorithm That Changed AI Forever Backpropagation, the backbone of deep learning, may have exploded in the 1980s, but its origins go even deeper. 👀 🔬 In 1974, Paul Werbos first formalized backpropagation in his PhD thesis, creating a systematic way to compute gradients across multi-layer networks efficiently. At first, AI legends like Marvin Minsky were skeptical – they saw it as too computationally heavy and unreliable compared to simpler models
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Explainr AI on Instagram: "Backpropagation: The Algorithm That Changed AI Forever Backpropagation, the backbone of deep learning, may have exploded in the 1980s, but its origins go even deeper. 👀 🔬 In 1974, Paul Werbos first formalized backpropagation in his PhD thesis, creating a systematic way to compute gradients across multi-layer networks efficiently. At first, AI legends like Marvin Minsky were skeptical – they saw it as too computationally heavy and unreliable compared to simpler models
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Instagram
Instagram
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Instagram
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Instagram
Artificial Intelligence | AI on Instagram: "Backpropagation is an important algorithm used to train neural networks, letting them learn from data by adjusting their parameters/weights. Backpropagation helps the network understand how changes to its parameters affect the overall loss/cost. This is where the chain rule from calculus comes in. Backpropagation works by computing how the error at the output layer flows backward through the network, layer by layer. It allows the model to compute piece
Artificial Intelligence | AI on Instagram: "Backpropagation is an important algorithm used to train neural networks, letting them learn from data by adjusting their parameters/weights. Backpropagation helps the network understand how changes to its parameters affect the overall loss/cost. This is where the chain rule from calculus comes in. Backpropagation works by computing how the error at the output layer flows backward through the network, layer by layer. It allows the model to compute piece
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Instagram
Artificial Intelligence | AI on Instagram: "Backpropagation is an important algorithm used to train neural networks, letting them learn from data by adjusting their parameters/weights. Backpropagation helps the network understand how changes to its parameters affect the overall loss/cost. This is where the chain rule from calculus comes in. Backpropagation works by computing how the error at the output layer flows backward through the network, layer by layer. It allows the model to compute piece
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Instagram
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Neural AI on Instagram: "Backpropagation is an important algorithm used to train neural networks, letting them learn from data by adjusting their parameters/weights. Backpropagation helps the network understand how changes to its parameters affect the overall loss/cost. This is where the chain rule from calculus comes in. Backpropagation works by computing how the error at the output layer flows backward through the network, layer by layer. It allows the model to compute pieces of the derivative
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Instagram
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Savita bhabhi on Instagram: "Viral caption ⬇️ . . An **algorithm** is a step-by-step set of instructions designed to solve a problem or perform a computation. It serves as the foundation for computer programs, data processing, and automated decision-making. **Key Characteristics** 1. **Precision** – Must have clear, unambiguous steps. 2. **Finiteness** – Must terminate after a finite number of steps. 3. **Input & Output** – Takes inputs, processes them, and produces outputs. 4. **Effectiveness**
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