Portál ZČU > Courseware > KIV > ANLP

Anonymous user Login Česky

HelpDesk - user support contact

Drobečková navigace

Portál ZČU > Courseware > Předměty po fakultách > Fakulta aplikovaných věd > KIV > ANLP > Study Materials

ANLP

Navigace

KIV/ANLP

Advanced Natural Language Processing

Guarantors: Ing. Miloslav Konopík, Ph.D.

Course literature KIV/ANLP -IS/STAG

Basic
Jurafsky, Daniel; Martin, James H., Speech and language processing : an introduction to natural language processing, computational linguistics, and speech recognition , Upper Saddle River 2009
Recommended
Yoav Goldberg, A Primer on Neural Network Models for Natural Language Processing 2015
Ian Goodfellow, Yoshua Bengio, Aaron Courville, Deep Learning (Adaptive Computation and Machine Learning series) , MIT press 2016
François Chollet, Deep Learning with Python 2017
Christopher D. Manning and Hinrich Schütze, Foundations of Statistical Natural Language Processing 1999
Aurélien Géron, Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 2017
Jacob Eisenstein, Introduction to Natural Language Processing (Adaptive Computation and Machine Learning series) 2019
Delip Rao, Brian McMahan, Natural Language Processing with PyTorch: Build Intelligent Language Applications Using Deep Learning

Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Deep Learning, MIT Press, On-line zde.

Stanford Lecture: Deep Learning for Natural Language Processing cs224n (YouTube)

Yoav Goldberg: Neural Network Methods for Natural Language Processing, Springer 2017.

Jacob Eisenstein: Natural Language Processing MIT Press, On-line zde

Delip Rao and Brian McMahan: Natural Language Processing with PyTorch: Build Intelligent Language Applications Using Deep Learning, Free-trial, examples.

PyTorch colab course: link.

Palková, Zdena. Fonetika a fonologie češtiny. Praha: Karolinum, 1994. ISBN: 80-7066-843-1.

Last updated: 18.09.2022

Studijní materiály

Natural language processing (NLP) and using the machine learning approach for this task. (258KB)

> Courseware > KIV > ANLP > Study Materials - Portál ZČU