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Course Description
This course is a project-based course that studies basic techniques for processing text data. The course will introduce the concepts of language morphology, text representation, pre-processing, feature extraction to obtain information such as similarity and text clustering. Topics covered include: language morphology, string representation, regex, tokenization, text pre-processing, Bag of Words, TF-IDF, word similarity, word clustering, and web scraping. Students will create group projects to apply text processing theories and concepts to problems in the field of Data Science.
Program Objectives (PO)
- Menjelaskan konsep Language Modeling dalam pengolahan teks
- Mampu merepresentasikan pengetahuan linguistik pada tingkat representasi morfologi, sintaksis serta semantik
- Mampu melakukan penggalian data teks dari sumber digital dan mengolahnya menggunakan teknik pre-processing, ekstraksi fitur, dan klasifikasi teks
- Mampu merancang penyelesaian masalah pada data teks menggunakan pengolahan data teks yang terkait
Aktifitas Pembelajaran
-
Pertemuan 1 Konsep morfologi bahasa mulai dari fonem, morpheme, lexemes, syntax, dan contex -
Pertemuan 2 Represesntasi string, operasi string, regex, dan visualisasi data teks pada pemrograman -
Pertemuan 3 Melakukan Web Scraping (HTTP) -
Pertemuan 4 Melakukan Web Scraping (API) -
Pertemuan 5 Melakukan teknik pre-prosesing data teks -
Pertemuan 6 Melakukan teknik pre-prosesing data teks -
Pertemuan 7 Melakukan teknik ekstraksi fitur pada data teks -
Pertemuan 8 Melakukan teknik ekstraksi fitur pada data teks -
Pertemuan 9 Melakukan teknik ekstraksi fitur pada data teks -
Pertemuan 10 Melakukan teks similarity pada data teks -
Pertemuan 11 Melakukan teks clustering pada data teks -
Pertemuan 12 Teknik pemrosesan data pada permasalahan nyata -
Pertemuan 13 Teknik pemrosesan data pada permasalahan nyata -
Pertemuan 14 Teknik pemrosesan data pada permasalahan nyata -
Pertemuan 15 Teknik pemrosesan data pada permasalahan nyata -
Pertemuan 16 Ujian Akhir Semester (UAS)
References
- Daniel Jurafsky & James H. Martin, Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, 2nd Edition, Prentice Hall, 2008.
- Sarkar, Dipanjan, Text Analytics with Python A Practitioner's Guide to Natural Language Processing, Second Edition, Apress, 2019
Lecturer
Difficult Things About Education.
$75$10
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