Oreilly – Getting Started with Natural Language Processing 2022-9

Description

Getting Started with Natural Language Processing course (reading from the book). This course is a comprehensive and easy-to-use guide to getting started with Natural Language Processing (NLP). Using this course, you can teach your computer to understand human language. This course is designed for people who want to enhance their applications with features such as data mining, user profiling, and automatic topic tagging.

In today’s world, from smart speakers to customer service chatbots, apps that understand text and speech are everywhere. Natural Language Processing (NLP) is the key to this powerful human-computer interaction. A new generation of tools and techniques has made it easier than ever to get started with NLP. This book teaches you how to enhance user-facing applications with text- and speech-based features. With easy-to-understand explanations and practical examples in this book, you’ll learn how to apply NLP to sentiment analysis, user profiling, and more. Each new project builds on what you’ve learned before and introduces new concepts and skills. Helpful diagrams and intuitive Python code examples make it easy to get started even for people with no machine learning background.

What you will learn:

• Basic concepts and algorithms of natural language processing
• Extracting information from raw text
• Useful Python libraries for natural language processing
• Subject tagging
• Building a search algorithm

This course is suitable for people who:

• Have basic Python skills.
• They have no previous experience in natural language processing.

Course details

• Publisher: Oreilly
• Lecturer: Ekaterina Kochmar
• Training level: beginner to advanced
• Training duration: 15 hours and 2 minutes

Course headings

• Chapter 1. Introduction
• Chapter 2. Your first NLP example
• Chapter 3. Introduction to information search
• Chapter 4. Information extraction
• Chapter 5. Author profiling as a machine-learning task
• Chapter 6. Linguistic feature engineering for author profiling
• Chapter 7. Your first sentiment analyzer using sentiment lexicons
• Chapter 8. Sentiment analysis with a data-driven approach
• Chapter 9. Topic analysis
• Chapter 10. Topic modeling
• Chapter 11. Named-entity recognition

Images of the Getting Started with Natural Language Processing course

Sample video of the course

download link

Download part 1 – 1 GB

Download part 2 – 1 GB

Download part 3 – 371 MB

File(s) password: www.downloadly.ir

File size

2.3 GB