Stochastic Gradient Descent Tutorial - 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 views3 weeks ago

MichaeL | Teaching myself ML on Instagram: "Using gradient descent in logistic regression. ⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️ —-——-——-——-——-——-——-——-— **Study Group Info** Want to master Machine Learning? ➡️Comment “Study” to join my exclusive study group** —-——-——-——-——-——-——-——-— ⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️ —- ⏳ 1 H —- #math #ml #ai #machinelearning #artificialintelligence #DataScience #computerscience"

MichaeL | Teaching myself ML on Instagram: "Using gradient descent in logistic regression. ⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️⬇️ —-——-——-——-——-——-——-——-— **Study Group Info** Want to master Machine Learning? ➡️Comment “Study” to join my exclusive study group** —-——-——-——-——-——-——-——-— ⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️⬆️ —- ⏳ 1 H —- #math #ml #ai #machinelearning #artificialintelligence #DataScience #computerscience"

83.9K views7 months ago

Gradient Descent optimizer in Deep Learning

Gradient Descent optimizer in Deep Learning

4.7K viewsDec 6, 2023

YouTubeOurSubject

Stochastic Gradient Descent (SGD) is the heart of machine learning optimization! By updating weights in small steps, it ensures faster and efficient learning for models. Simplicity with power! 🚀 #SGD #MachineLearning #Optimization

Stochastic Gradient Descent (SGD) is the heart of machine learning optimization! By updating weights in small steps, it ensures faster and efficient learning for models. Simplicity with power! 🚀 #SGD #MachineLearning #Optimization

202 views9 months ago

TikTokyazilimciabi

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 views6 months ago

Instagramdeeply.ai

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

40 viewsAug 27, 2024

YouTubeNeural Nexus

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

3.6K views7 months ago

Understanding Gradient Descent in AI

93 views6 months ago

YouTubeSynaptigon

Gradient Descent Vs Stochastic Gradient Descent

401 viewsMar 25, 2024

YouTubeEduFlair KTU CS

How Stochastic Indicator Works (Learn It in 1 Minute!)

20.3K viewsNov 7, 2020

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

5.2K views5 months ago

Ashish Singh on Instagram: "Stochastic Gradient Descent out here skipping the queue, making educated guesses, and still reaching the loss minimum faster than your weekend plans! 😅 #StochasticGradientDescent #MachineLearningHumor #DeepLearning #BioinformaticsJokes #MiniBatchMadness #OptimizerOnTheLoose #LossFunctionChronicles #MLLife #FastButFuzzy"

12.1K views1 month ago

AI | Machine Learning | Tech on Instagram: "Stochastic Gradient Descent (SGD) is an optimization method used to minimize a function, usually a loss function, to improve a model. Think of it like trying to get to the lowest point of a hill: the gradient represents the slope, telling you which direction to move to go down. Instead of looking at the entire hill (or dataset), SGD picks small random subsets of data at each step, calculating the gradient based on that subset. This makes updates faster

5.6K views2 months ago

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 views1 week 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

154.9K 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 views1 week 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

AI | Machine Learning | Tech on Instagram: "Gradient descent is an optimization algorithm that minimizes a function by iteratively stepping toward its lowest value. It works by taking steps proportional to the negative gradient (slope) of the function at the current point, moving in the direction of steepest descent. This process continues until the function reaches its minimum or the steps become negligibly small. Credit: @3blue1brown #machinelearning #deeplearning #math #neuralnetwork #datasci

2.3K views1 month 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

AI • Machine Learning • Tech on Instagram: "Stochastic Gradient Descent (SGD) is an optimization method used to minimize a function, usually a loss function, to improve a model. Think of it like trying to get to the lowest point of a hill: the gradient represents the slope, telling you which direction to move to go down. Instead of looking at the entire hill (or dataset), SGD picks small random subsets of data at each step, calculating the gradient based on that subset. This makes updates faster

41K views5 months ago

Artificial Intelligence | AI on Instagram: "Backpropagation is the algorithm used to compute gradients in neural networks, making it a crucial component of gradient descent. It works by applying the chain rule of calculus to propagate the error from the output layer back through the network, calculating how much each weight contributed to the total loss. Once these gradients are computed, they are used in the gradient descent update step: each weight is adjusted by subtracting the gradient multi

17.7K views3 months ago

Artificial Intelligence | AI on Instagram: "Stochastic Gradient Descent (SGD) is an optimization method used to minimize a function, usually a loss function, to improve a model. Think of it like trying to get to the lowest point of a hill: the gradient represents the slope, telling you which direction to move to go down. Instead of looking at the entire hill (or dataset), SGD picks small random subsets of data at each step, calculating the gradient based on that subset. This makes updates faster

4K views4 months ago

Artificial Intelligence | AI on Instagram: "Stochastic Gradient Descent (SGD) is an optimization method used to minimize a function, usually a loss function, to improve a model. Think of it like trying to get to the lowest point of a hill: the gradient represents the slope, telling you which direction to move to go down. Instead of looking at the entire hill (or dataset), SGD picks small random subsets of data at each step, calculating the gradient based on that subset. This makes updates faster

21K views1 month ago

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