Gradient Descent Variants with Tutorial Video Example - Search Videos

Artificial Intelligence | AI on Instagram: "Gradient descent is a fundamental optimization algorithm used by most AI models to learn from data by minimizing a loss function, which measures how far the model’s predictions are from the true values. Conceptually, it treats the loss function as a landscape (we call this the loss landscape) with peaks and valleys representing high and low errors. At any point on this landscape, the gradient (vector of slopes) indicates the direction and steepness of

Artificial Intelligence | AI on Instagram: "Gradient descent is a fundamental optimization algorithm used by most AI models to learn from data by minimizing a loss function, which measures how far the model’s predictions are from the true values. Conceptually, it treats the loss function as a landscape (we call this the loss landscape) with peaks and valleys representing high and low errors. At any point on this landscape, the gradient (vector of slopes) indicates the direction and steepness of

7.6K views4 weeks ago

Gradient Descent optimizer in Deep Learning

Gradient Descent optimizer in Deep Learning

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How the gradient function/derivative can be used to find the gradient - Example - Part 02

How the gradient function/derivative can be used to find the gradient - Example - Part 02

YouTubeEdexcel Mathematics Kingdom

Batch Gradient Descent Weight Updates 🏋️ - Deep Learning Beginner 👶 📈 - Topic 102

Batch Gradient Descent Weight Updates 🏋️ - Deep Learning Beginner 👶 📈 - Topic 102

939 viewsMar 17, 2024

YouTubedeeplizard

Gradient Descent The Heart of Neural Network Optimization Explained

Gradient Descent The Heart of Neural Network Optimization Explained

34 views7 months ago

Deeply AI: AI, ChatGPT, Robotics, Data Science on Instagram: "Gradient descent is an optimization method in deep learning that helps a model improve its predictions by adjusting its weights and biases. It works by measuring the error between the actual and predicted values using a cost function. The algorithm calculates the gradient (slope) of the cost function and updates the parameters by moving in the opposite direction of the gradient. The size of each step is controlled by a learning rate.

Deeply AI: AI, ChatGPT, Robotics, Data Science on Instagram: "Gradient descent is an optimization method in deep learning that helps a model improve its predictions by adjusting its weights and biases. It works by measuring the error between the actual and predicted values using a cost function. The algorithm calculates the gradient (slope) of the cost function and updates the parameters by moving in the opposite direction of the gradient. The size of each step is controlled by a learning rate.

5K views7 months ago

Instagramdeeply.ai

Master Gradient Descent Machine Learning's Fit Trainer

Master Gradient Descent Machine Learning's Fit Trainer

101 viewsAug 4, 2024

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Training AI Models: From Data to Decisions #ai #technology #trending #trendingshorts #viralvideo

40 viewsAug 27, 2024

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Gradient Descent visualized #datascience #machinelerning #deeplearning #ai #math

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Understanding Gradient Descent in AI

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Gradient Descent Vs Stochastic Gradient Descent

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Artificial Intelligence | AI on Instagram: "Gradient descent is a fundamental optimization algorithm used by most AI models to learn from data by minimizing a loss function, which measures how far the model’s predictions are from the true values. Conceptually, it treats the loss function as a landscape (we call this the loss landscape) with peaks and valleys representing high and low errors. At any point on this landscape, the gradient (vector of slopes) indicates the direction and steepness of

20.6K views2 months ago

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AI • Machine Learning • Tech on Instagram: "Gradient descent is an optimization algorithm widely used in machine learning to minimize a loss function, which is a measure of how well a model’s predictions match the actual outcomes. In the gradient descent process, the model iteratively adjusts its parameters (its weights and biases) to reduce the loss. The parameters are adjusted based on the gradient, or partial derivatives, of the loss function with respect to each parameter. The gradient point

50.3K views3 months ago

Instagramaibutsimple

e-Train Brain Academy on Instagram: "Gradient Descent is an optimization algorithm used to minimize the loss (or error) in machine learning models by updating the model’s parameters (like weights) in the direction that reduces the loss. 🧠 How It Works (in simple terms): Imagine you're standing on a hill and want to get to the lowest point in the valley (the minimum of a function). You look around, figure out the steepest downward direction (the negative gradient), and take a small step that way

1.8K views1 month ago

Insightforge | Data Science & AI on Instagram: "Gradient Descent: how AI models actually learn At the core of most AI training lies gradient descent, an algorithm that minimizes a loss function — the measure of how far predictions are from the truth. Think of the loss function as a landscape of hills and valleys: High peaks = big errors Low valleys = small errors The gradient shows the steepest uphill direction. Gradient descent simply moves the opposite way — downhill — step by step, adjusting

1.9K views2 weeks ago

AI • Machine Learning • Tech on Instagram: "In deep learning, gradient descent is an optimization algorithm (or optimizer) that adjusts the model’s weights and biases iteratively to minimize some cost function. This cost function is used to measure the error between the correct label and the model’s prediction. By computing the gradient of the cost function with respect to these parameters, the algorithm computes the direction of steepest descent. To reduce the cost, it takes small “steps” in th

39.6K views7 months ago

40.8K viewsAug 21, 2024

Instagramaibutsimple

AI • Machine Learning • Tech on Instagram: "Gradient descent is a fundamental optimization algorithm used by most AI models to learn from data by minimizing a loss function, which measures how far the model’s predictions are from the true values. Conceptually, it treats the loss function as a landscape (we call this the loss landscape) with peaks and valleys representing high and low errors. At any point on this landscape, the gradient (vector of slopes) indicates the direction and steepness of

156.4K views2 months ago

Artificial Intelligence | AI on Instagram: "Gradient descent is a fundamental optimization algorithm used by most AI models to learn from data by minimizing a loss function, which measures how far the model’s predictions are from the true values. Conceptually, it treats the loss function as a landscape (we call this the loss landscape) with peaks and valleys representing high and low errors. At any point on this landscape, the gradient (vector of slopes) indicates the direction and steepness of

4.9K views2 weeks ago

AI | Machine Learning | Tech on Instagram: "In deep learning, gradient descent is an optimization algorithm (or optimizer) that adjusts the model’s weights and biases iteratively to minimize some cost function. This cost function is used to measure the error between the correct label and the model’s prediction. By computing the gradient of the cost function with respect to these parameters, the algorithm computes the direction of steepest descent. To reduce the cost, it takes small “steps” in th

3.8K views2 months ago

Neural AI on Instagram: "Gradient descent is a fundamental optimization algorithm used by most AI models to learn from data by minimizing a loss function, which measures how far the model’s predictions are from the true values. Conceptually, it treats the loss function as a landscape (we call this the loss landscape) with peaks and valleys representing high and low errors. At any point on this landscape, the gradient (vector of slopes) indicates the direction and steepness of the fastest increas

2.9K views2 months ago

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