Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python

By:

Kulkarni, Akshay

Contributor(s):

Shivananda, Adarsha

Publication details: Apress 2024Description: xxvi, 283pISBN:

9781484285299

Subject(s):

DDC classification:

006.3/KUL/SHI

Summary: Natural Language Processing Recipes starts by offering solutions for cleaning and preprocessing text data and ways to analyze it with advanced algorithms. You’ll see practical applications of the semantic as well as syntactic analysis of text, as well as complex natural language processing approaches that involve text normalization, advanced preprocessing, POS tagging, and sentiment analysis. You will also learn various applications of machine learning and deep learning in natural language processing. By using the recipes in this book, you will have a toolbox of solutions to apply to your own projects in the real world, making your development time quicker and more efficient.

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Holdings
Item type	Current library	Call number	Status	Notes	Date due	Barcode
Books	Symbiosis Institute of Computer Studies and Research Data Mining	006.3/KUL/SHI (Browse shelf(Opens below))	Available	Data scientists who want to refresh and learn various concepts of natural language processing through coding exercises.		SICSR-B-19668

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	005.741/KAN DATA MINING: CONCEPTS, MODELS, METHODS AND ALGORITHMS	006.3/HAL Managing AI in the Enterprise	006.3/KUL/SHI Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python	006.3/MIC Applied Deep Learning with TensorFlow 2: Learn to Implement Advanced Deep Learning Techniques with Python	006.3/SAN Deep Reinforcement Learning with Python	006.3/VER Computer Vision Using Deep Learning: Neural Network Architectures with Python and Keras	Next

Natural Language Processing Recipes starts by offering solutions for cleaning and preprocessing text data and ways to analyze it with advanced algorithms. You’ll see practical applications of the semantic as well as syntactic analysis of text, as well as complex natural language processing approaches that involve text normalization, advanced preprocessing, POS tagging, and sentiment analysis. You will also learn various applications of machine learning and deep learning in natural language processing.
By using the recipes in this book, you will have a toolbox of solutions to apply to your own projects in the real world, making your development time quicker and more efficient.

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