Answer / Amber Goel

Machine Learning (ML) encompasses a broad set of techniques for teaching computers to learn from data. It includes simple algorithms like linear regression, decision trees, and support vector machines.Deep Learning is a subset of ML that uses neural networks with multiple layers to learn complex representations of data. While traditional machine learning algorithms require manual feature engineering, deep learning models can automatically extract features from raw data.

Describe the theory of autonomous form of deep learning in a few words.

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What are the applications of deep learning?

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What do you understand by Backpropagation?

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Is rtx 2060 good for deep learning?

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What is Gradient Descent?

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why do we need data normalization?

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What is Bagging and Boosting?

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What are some factors that explain the success and recent rise of deep learning?

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Is 8gb ram enough?

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What are the unsupervised learning algorithms in deep learning?

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What do you understand by a convolutional neural network?

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What do you understand by autoencoder?

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