What are the main benefits of mini-batch gradient descent?
Answer / Prandeep Kaur
Mini-batch Gradient Descent is an optimization technique that allows for efficient training of large neural networks. Its main benefits include reducing memory usage, allowing parallel computation, and enabling faster convergence to a local minimum.
| Is This Answer Correct ? | 0 Yes | 0 No |
What is matrix element-wise multiplication? Explain with an example.
Explain a Computational Graph.
How many layers in the neural network?
What is meant by deep learning?
What is the most used activation function?
What are Hyperparameters?
Explain the following variant of gradient descent: stochastic, batch, and mini-batch?
What is deep learning, and how does it contrast with other machine learning algorithms?
What is the function of the fourier transform in deep learning?
Explain gradient descent?
Is 16gb of ram a lot?
What is relu function?
AI Algorithms (74)
AI Natural Language Processing (96)
AI Knowledge Representation Reasoning (12)
AI Robotics (183)
AI Computer Vision (13)
AI Neural Networks (66)
AI Fuzzy Logic (31)
AI Games (8)
AI Languages (141)
AI Tools (11)
AI Machine Learning (659)
Data Science (671)
Data Mining (120)
AI Deep Learning (111)
Generative AI (153)
AI Frameworks Libraries (197)
AI Ethics Safety (100)
AI Applications (427)
AI General (197)
AI AllOther (6)