What Is JavaScript Used For?
September 30, 2024
Article
New year. Big goals. Bigger savings. Unlock a year of unlimited access to learning with Coursera Plus for $199. Save now.
This course is part of Natural Language Processing with Real-World Projects Specialization
Instructor: Packt - Course Instructors
Included with
Recommended experience
Intermediate level
For aspiring NLP practitioners, data scientists, and software engineers. Basic Python and machine learning knowledge recommended.
Recommended experience
Intermediate level
For aspiring NLP practitioners, data scientists, and software engineers. Basic Python and machine learning knowledge recommended.
Remember the basics of NLP and text encoding.
Apply regular expressions for text processing.
Implement lexical processing techniques like bag-of-words and Tf-IDF.
Create models for spelling correction and handling combined words.
Add to your LinkedIn profile
September 2024
4 assignments
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
Begin your journey into Natural Language Processing (NLP) with an introduction to text data and encoding techniques, delving into the intricacies of regular expressions through extensive practice and use cases. Progress to lexical processing, learning to handle stopwords, split words, and implement bag-of-words and Tf-IDF models, applying these techniques to tasks like spam detection through detailed case studies.
Advance to sophisticated lexical processing topics like spelling correction models and the Soundex algorithm, exploring practical implementations via Levenshtein Distance and spell correctors, and tackling challenges such as handling combined words like "New Delhi." This section solidifies your ability to preprocess and clean text data effectively. Transition to syntactic processing, covering parsing and grammar for English sentences, intermediate topics like stochastic parsing, the Viterbi algorithm, and Hidden Markov Models, reinforced through case studies and practical applications. Finally, tackle advanced syntactic processing techniques, including CFG grammar, top-down and bottom-up parsing, and probabilistic approaches like PCFG, concluding with a real-world project on information extraction through a comprehensive case study on ATIS flight reservations. Designed for aspiring NLP practitioners, data scientists, and software engineers, this course enhances understanding of syntactic processing, with a basic knowledge of Python programming and familiarity with machine learning concepts recommended.
In this module, we will introduce the foundational concepts of Natural Language Processing (NLP) and delve into the mechanics of regular expressions (Regex). We will explore how to handle text data effectively and encode text for further processing. The module also includes a comprehensive look at Regex through multiple parts, culminating in practical use cases to solidify your understanding.
11 videos2 readings
In this module, we will explore the basics of lexical processing, starting with stopwords and word splitting techniques. We'll dive into the bag-of-words model and its application, followed by handling similar text words. The module concludes with case studies on applying these techniques in real-world scenarios, including spam detection and Tf-IDF analysis.
9 videos
In this module, we will tackle more complex lexical processing tasks such as correcting spelling mistakes and using the Soundex algorithm for phonetic indexing. We will also work on case studies to implement these techniques practically. The module includes building spell correctors and handling combined words, providing a robust understanding of advanced lexical processing methods.
10 videos1 assignment
In this module, we will cover the basics of syntactic processing, starting with an understanding of what it entails. We'll look at parsing techniques and work on grammar rules for English sentences. The module includes case studies that apply lexicon-based and rule-based tagging techniques, helping you grasp the foundational aspects of syntactic analysis.
6 videos
In this module, we will delve into intermediate syntactic processing, focusing on stochastic parsing and the Viterbi algorithm. We'll explore Hidden Markov Models and tackle decoding problems. The module includes case studies on Part-of-Speech (POS) tagging, HMMs, and the Viterbi algorithm, providing hands-on experience in intermediate syntactic processing.
9 videos
In this module, we will cover advanced syntactic processing techniques, including addressing issues with shallow parsing. We'll work with context-free grammar (CFG) and probabilistic CFG, and explore top-down and bottom-up parsing methods. The module includes detailed case studies, helping you understand practical issues and solutions in advanced syntactic processing.
10 videos1 assignment
In this module, we will focus on probabilistic approaches to syntactic processing. We will cover probabilistic context-free grammar (PCFG), and engage in case studies to apply these methods. The module also includes Chomsky Normal Form and dependency parsing techniques, providing a comprehensive understanding of probabilistic syntactic processing.
5 videos
In this module, we will apply syntactic processing techniques to a real-world project, focusing on information extraction. We'll start with an introduction to the project and proceed with detailed case studies, specifically using ATIS flight reservations. This module is designed to consolidate your knowledge and skills by working through a comprehensive, practical application of syntactic processing.
7 videos1 reading2 assignments
Packt helps tech professionals put software to work by distilling and sharing the working knowledge of their peers. Packt is an established global technical learning content provider, founded in Birmingham, UK, with over twenty years of experience delivering premium, rich content from groundbreaking authors on a wide range of emerging and popular technologies.
DeepLearning.AI
Specialization
Course
Edureka
Course
DeepLearning.AI
Course
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
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.
If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.
This course is one of a few offered on Coursera that are currently available only to learners who have paid or received financial aid, when available.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.