Titlebook: Machine and Deep Learning Algorithms and Applications; Uday Shankar Shanthamallu,Andreas Spanias Book 2022 Springer Nature Switzerland AG

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978-3-031-03748-1Springer Nature Switzerland AG 2022

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Synthesis Lectures on Signal Processinghttp://image.papertrans.cn/m/image/620799.jpg

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Conclusion and Future Directions,s organized to cover algorithms and concepts first. It later describes the applications of ML algorithms in various fields, including signal processing, image and computer vision, natural language processing, speech and audio processing, energy, health, security, and defense applications.

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Introduction to Machine Learning,rained on thousands of images of dogs and cats until it can learn to distinguish the two. Similarly, for spam email filtering, an ML model can be trained with a lot of benign and spam emails to filter future spam messages.

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Supervised Learning, a labeled input dataset termed . Once the model achieves the desired performance on training data, the trained model is then used to perform inference on unseen data. The data that has not been used for training and thus unseen by the model is termed

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Book 2022. We begin by describing how machine learning provides capabilities to computers and embedded systems to learn from data. A typical machine learning algorithm involves training, and generally the performance of a machine learning model improves with more training data. Deep learning is a sub-area of

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