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Lecture “Natural language processing - Chapter 1: Introduction and Overview of NLP” has contents: Introduce some of the classical problems in NLP, learn to address empirical problems, talk/write clearly about your work, decision and observations. | Trường Đại học Công nghiệp Tp. HCM Khoa Công nghệ thông tin (Faculty of Information Technology) N.L.P. NATURAL LANGUAGE PROCESSING Teacher: Lê Ngọc Tấn Email: letan.dhcn@gmail.com Blog: http://lengoctan.wordpress.com CONTENT Chapter 1. Introduction and Overview of NLP Chapter 2. Fundamental algorithms and mathematical models Chapter 3. Basic principles for NLP Chapter 4. Computational Linguistics Chapter 5. Foundation of Statistical Machine Translation C.1 – Introduction and Overview of NLP NLP. p.2 Chapter 1 Introduction and Overview of NLP C.1 – Introduction and Overview of NLP NLP. p.3 In NLP module, we will Introduce some of the classical problems in NLP Learn to address empirical problems – Is one system for a task better than another – Understand where and how a system fails – Propose possible solutions Talk/write clearly about your work, decision and observations C.1 – Introduction and Overview of NLP NLP. p.4 What background do I need? No background in NLP is required Expect to know a bit of basic probability (know Bayes rules) Know a bit about vectors and vector space, a bit of calculus (matrices) Have reasonable programming ability (know about hash tables and graph data structures, Java, Python, Perl, Prolog, ) C.1 – Introduction and Overview of NLP NLP. .
