Natural Language Processing (CS 445)

2021 Spring
Faculty of Engineering and Natural Sciences
Computer Sci.& Eng.(CS)
3
6
Reyyan Yeniterzi reyyan@sabanciuniv.edu,
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English
Undergraduate
CS204 CS210
Formal lecture
Interactive,Learner centered,Project based learning
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CONTENT

This course studies the theory, design and implementation of natural language processing systems. Topics include text processing, regular expressions, statistical properties of text, edit distance, language modeling, text classification, sequence modeling, topic modeling, computational morphology, neural networks for NLP, chatbots, transfer learning for NLP.

OBJECTIVE

A student who succesfully fulfills the course requirements will be able to demonstrate:
1) To describe the statistical properties of text in natural language.
2) To implement programs that can process textual data and extract valuable information from it.
3) To apply well-known language processing techniques to text.
4) To explain the significance and principles of language modeling.
5) To develop machine learning models to classify documents, sub-documents or terms.
6) To assess the quality of natural language processing models applied to text.

LEARNING OUTCOMES

  • To describe the statistical properties of text in natural language.
  • To implement programs that can process textual data and extract valuable information from it.
  • To apply well-known language processing techniques to text.
  • To explain the significance and principles of language modeling.
  • To develop machine learning models to classify documents, sub-documents or terms.
  • To assess the quality of natural language processing models applied to text.

PROGRAMME OUTCOMES


1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 1

2. Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 1

3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects; have the ability to continue to educate him/herself. 3

4. Communicate effectively in Turkish and English by oral, written, graphical and technological means. 3

5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 3


1. Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 5

2. Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose. 5

3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively. 5

4. Have the ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 4

5. Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 4

6. Possess knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 1

7. Possess knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; knowledge of behavior according to ethical principles, understanding of professional and ethical responsibility. 2

8. Have the ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. 4


1. Comprehend key concepts in biology and physiology, with emphasis on molecular genetics, biochemistry and molecular and cell biology as well as advanced mathematics and statistics. 1

2. Develop conceptual background for interfacing of biology with engineering for a professional awareness of contemporary biological research questions and the experimental and theoretical methods used to address them. 1


1. Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 5

2. Demonstrate knowledge of discrete mathematics and data structures. 2

3. Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 5


1. Use mathematics (including derivative and integral calculations, probability and statistics, differential equations, linear algebra, complex variables and discrete mathematics), basic sciences, computer and programming, and electronics engineering knowledge to (a) Design and analyze complex electronic circuits, instruments, software and electronics systems with hardware/software or (b) Design and analyze communication networks and systems, signal processing algorithms or software 3


1. Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 1

2. Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 1

3. Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 1


1. Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic tools of industrial engineering such as modeling and optimization, stochastics, statistics. 2

2. Design and develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy. 2

3. Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools. 2

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Midterm 30
Quiz 20
Individual Project 50

RECOMENDED or REQUIRED READINGS

Optional Readings

Speech and Language Processing by Daniel Jurafsky and James Martin.
Foundations of Statistical Natural Language Processing by Christopher Manning and Hinrich Sch├╝tze
Natural Language Processing with Python by Steven Bird, Ewan Klein and Edward Loper