Autoencoders are neural networks that learn to compress input data into a lower-dimensional representation and then reconstruct it back, useful

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Recurrent Neural Networks (RNNs) are a type of neural network designed for sequential data, where outputs from previous steps are

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Cloud computing is the delivery of computing services like servers, storage, databases, networking, software, and more over the internet. It

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Convolutional Neural Networks (CNNs) are deep learning models designed to process grid-like data such as images by applying convolutional filters

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Hadoop is an open-source framework used for processing and storing large-scale data across distributed systems. It includes HDFS for storage,

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Hadoop uses various data formats and tools like Streaming and Pipes to analyze and scale data processing efficiently. It relies

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Autoencoders are neural networks that learn to compress and reconstruct input data, mainly used for dimensionality reduction and feature learning.

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