Hands-On Natural Language Processing
Hands-On Natural Language Processing
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 50m | 144 MB
Instructor: Wuraola Oyewusi
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 50m | 144 MB
Instructor: Wuraola Oyewusi
Dexterity at deriving insight from text data is a competitive edge for businesses and individual contributors. This course with instructor Wuraola Oyewusi is designed to help developers make sense of text data and increase their relevance. This is a hands-on course teaching practical application of major natural language processing tasks. Learn how to replicate the knowledge gained into the data that you work with. This course includes a background of each task’s process flow, use cases, and a coding demo. Some of the topics covered are named entity recognition, text summarization, topic modeling, and sentiment analysis.
Learning objectives
- Interpret how entities are tagged when annotating data.
- Develop a topic modeling algorithm that accurately categorizes items.
- Identify text summarization techniques.
- Differentiate between the three main categories of classification by polarity.
- Recognize unique characteristics and advantages of transformer-based models for sentiment analysis.
Hands-On Natural Language Processing
