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Hands-On Natural Language Processing with Python by Rajalingappaa Shanmugamani, Rajesh Arumugam

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To get the most out of this book

The prerequisites for the book are basic knowledge of ML or deep learning and intermediate Python skills, although both are not mandatory. We have given a brief introduction to deep learning, touching upon topics such as multi-layer perceptrons, Convolutional Neural Networks (CNNs), and RNNs in Chapter 1, Getting Started. It would be helpful if the reader knows general ML concepts, such as overfitting and model regularization, and classical models, such as linear regression and random forest. In more advanced chapters, the reader might encounter in-depth code walkthroughs that expect at least a basic level of Python programming experience. 

All the code examples in the book can be downloaded from the code ...

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