Course Name: Natural Language Processing

Course abstract

This course starts with the basics of text processing including basic pre-processing, spelling correction, language modeling, Part-of-Speech tagging, Constituency and Dependency Parsing, Lexical Semantics, distributional Semantics and topic models. Finally, the course also covers some of the interesting applications of text mining such as entity linking, relation extraction, text summarization, text classification, sentiment analysis and opinion mining.


Course Instructor

Media Object

Prof. Pawan Goyal

Pawan Goyal joined the Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur as an Assistant Professor on July 30th, 2013. Prior to that, he was working at INRIA Paris-Rocquencourt as a post doctoral fellow with Prof. Gérard Huet on The Sanskrit Heritage Site. He did his B. Tech. in Electrical Engineering from Indian Institute of Technology, Kanpur. He received his Ph. D. from Intelligent Systems Research Centre, Faculty of Computing and Engineering, University of Ulster, UK. His main research interests include Text Mining, Natural Language Processing, Information Retrieval and Sanskrit Computational Linguistics. He has published over 40 research articles in various CS journals and conferences including ACL, Coling, TKDE, CACM, KDD, CIKM, JCDL.
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Teaching Assistant(s)

MAYANK SINGH

Doctor of Philosophy
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
IIT Kharagpur

AMRITH KRISHNA

Doctor of Philosophy
DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING
IIT Kharagpur

 Course Duration : Jan-Apr 2017
  View Course
 Enrollment : 01-Jan-2017 to 23-Jan-2017
 Exam registration : 15-Feb-2017 to 27-Mar-2017
 Exam Date : 23-Apr-2017

Enrolled

3648

Registered

122

Certificate Eligible

78

Certified Category Count

Gold

0

Silver

0

Elite

41

Successfully completed

37

Participation

25

Success

Elite

Gold




Legend

>=90 - Elite + Gold
60-89 - Elite
40-59 - Successfully Completed
<40 - No Certificate

Final Score Calculation Logic

  • Assignment Score = Average of best 8 out of 12 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
Natural Language Processing - Toppers list

SHABANA K M 84%

UNEMPLOYED

SOWMYA LAKSHMI B S 79%

BMS COLLEGE OF ENGINEERING

SRINATH B 78%

INDIAN INSTITUTE OF TECHNOLOGY MADRAS

PRAJIT T R 74%

M S RAMAIAH INSTITUTE OF TECHNOLOGY

B HARISH 72%

QUALCOMM INDIA PVT LTD

ABHISHEK JAIN 72%

MEDI-CAPS UNIVERSITY,INDORE

Enrollment Statistics

Total Enrollment: -1

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Registration Statistics

Total Registration : 132

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Will be updated shortly.!

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Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.