Books in Shelfclass 5.B.21, Machine learning/deep learning for linguistics:

Number of books: 15

Shelfclass	Sortkey	Title
5.B.21	AGGARWAL, CHARU C.	Machine Learning for Text
5.B.21	AMARATUNGA, THIMIRA	Understanding Large Language Models: Learning Their Underlying Concepts and Technologies
5.B.21	COHEN, SHAY	Bayesian Analysis in Natural Language Processing
5.B.21	DENG, LI	Deep Learning in Natural Language Processing
5.B.21	DROR, ROTEM	Statistical Significance Testing for Natural Language Processing
5.B.21	GANEGEDARA, THUSHAN	Natural Language Processing with TensorFlow: Teach language to machines using Python’s deep learning library
5.B.21	GOLBERG, YOAV	Neural Network Methods for Natural Language Processing
5.B.21	GOMEZ-PEREZ, JOSE MANUEL	A Practical Guide to Hybrid Natural Language Processing: Combining Neural Models and Knowledge Graphs for NLP
5.B.21	INDURKHYA, NITIN	Handbook of Natural Language Processing
5.B.21	KOEHN, PHILIPP	Neural Machine Translation
5.B.21	RAO, DELIP	Natural Language Processing with PyTorch: Build Intelligent Language Applications Using Deep Learning
5.B.21	SMITH, NOAH A.	Linguistic Structure Prediction
5.B.21	THANAKI, JALAJ	Python Natural Language Processing: Advanced machine learning and deep learning techniques for natural language processing
5.B.21	TUNSTALL, LEWIS	Natural Language Processing with Transformers: Building Language Applications with Hugging Face
5.B.21	WEISS, SHOLOM M.	Fundamentals of Predictive Text Mining