Abstract
Conventionally, many techniques of machine learning and signal processing have been used widely with structured architectures containing a single layer and thus a lack of multiple layers of features make it less efficient technique. Overcoming these challenges, deep learning has become a significant field in the areas like image analysis, object and speech recognition, big data, etc. Emerging technologies require a flexible and efficient tool to process large amount of data, thus making deep learning a powerful tool to work in the field of machine learning and artificial intelligence. Deep learning being considered as equivalent to the human brain in terms of processing, outperforms the conventional algorithms. These algorithms are linked directly to the neural networks algorithms and process data or information about the images by passing them through layersof neural networks. This paper addresses important algorithms of deep learning widely used like CNN, RNN, deep belief networks and deep neural networks.
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Raj, S. (2022). Deep Learning Algorithms. In: GarcÃa Márquez, F.P. (eds) International Conference on Intelligent Emerging Methods of Artificial Intelligence & Cloud Computing. IEMAICLOUD 2021. Smart Innovation, Systems and Technologies, vol 273. Springer, Cham. https://doi.org/10.1007/978-3-030-92905-3_15
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DOI: https://doi.org/10.1007/978-3-030-92905-3_15
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