Lecture Natural language processing: Chapter 1 – Lê Ngọc Tấn

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