Start your journey into advanced semantic processing with an introduction to fundamental concepts such as entities, arity, and reification. Learn about schemas and semantic associations, understanding how these elements form the backbone of semantic processing.
Advanced Semantic Processing
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Advanced Semantic Processing
This course is part of Natural Language Processing with Real-World Projects Specialization
Instructor: Packt - Course Instructors
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Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
5 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
What you'll learn
Understand the fundamental concepts of semantic processing.
Analyze and implement Latent Semantic Analysis (LSA).
Apply Word2vec techniques through practical case studies.
Evaluate and execute real-world projects on semantic processing.
Skills you'll gain
Details to know
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Recently updated!
September 2024
Assessments
1 assignment
Taught in English
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This course is part of the Natural Language Processing with Real-World Projects Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 3 modules in this course
In this module, we will delve into the foundational aspects of semantic processing. Starting with basic concepts and entities, we will explore the intricacies of arity, reification, and schemas. The module will also cover semantic associations, terms, concepts, and culminate with practical applications like WordNet and word sense disambiguation.
What's included
13 videos2 readings
In this module, we will introduce advanced topics in semantic processing, focusing on distributional semantics. We'll explore the concepts and applications of occurrence and co-occurrence matrices, delve into word vectors and their significance, and understand the metrics used to measure semantic similarity and differences.
What's included
9 videos
In this module, we will continue our exploration of advanced semantic processing techniques. We'll cover Latent Semantic Analysis (LSA) and Word2vec in depth, supported by multiple case studies to demonstrate their practical applications. Additionally, we will investigate the use of these techniques in various classification scenarios to solidify our understanding.
What's included
11 videos1 reading1 assignment
Instructor
Offered by
Recommended if you're interested in Machine Learning
Google Cloud
DeepLearning.AI
Coursera Project Network
University of Michigan
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.