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Explores Kernel Ridge Regression, the Kernel Trick, Representer Theorem, feature spaces, kernel matrix, predicting with kernels, and building new kernels.
Delves into the challenges and benefits of deep learning, highlighting the transition to convolutional neural networks and the impact of network width on the loss landscape.
Introduces the basics of text data analysis, covering document retrieval, classification, sentiment analysis, and topic detection using preprocessing techniques and machine learning models.
