- Basic understanding of mathematics
- Comprehensive course
- Hands-on tutorials
- Course resources included
- Beginners in python
- Working in with data analytics
- Anyone working with text mining
- Curious about data science
PROJECT BASED TEXT MINING IN PYTHON
Use of Natural Language Processing, Machine Learning and Sentiment Analysis towards Data Science
What will students learn in your course?
- In this course the students will learn the basics of text mining and will build on it to perform document categorization, document grouping and subjective analysis.
- The code implementation is carried out in Python language, while Natural Language Processing (NLP) is used for pre-processing textual data.
- We will learn about structuring textual data using different representation schemes and tuning their parameters.
- Starting from a very small dummy dataset, we migrate to existing databases to build models and perform validation and evaluation on them.
- We will learn about scraping data from the web and converting it into a dataset.
- Sentiment analysis of user hotel reviews
- Information extraction from raw documents
Dr. Taimoor Khan is an Assistant Professor in Computer Science. He has taught various courses to undergraduate and graduate students. He is particularly interested in courses relating to software design and development, databases, artificial intelligence, machine learning and data mining. His PhD research is related to data science and computational linguistics, having worked with large-scale textual data for building knowledge-based systems that are adaptive and evolve with the growing needs without having to be explicitly trained for a specific scenario. Dr. Khan has published papers in internationally recognized journals and conferences where he proposed solutions to real-world data analysis issues. He has supervised several projects that offered software based solutions for social content analytics, recommendations and tracking evolving public interests.
Participants receives course completion certificate from Research HUB upon finishing all lectures and MCQs within 01 to 30 weeks from the enrollment date. See sample certificate here HERE.
THE COURSE INCLUDES
- 66 on-demand lectures.
- Course resources included.
- Lifetime access to course resources and updates.
Please check course curriculum section for detail course plan. See Payment Options here.
The course contents are subject to copyright. Unauthorized distribution of the course contents will lead to legal actions by Research HUB. The enrolled participants will have lifetime access to the course materials and any future updates. For institutional subscription, contact us at firstname.lastname@example.org.