Hands-On Text Classification
Build text classifiers that work!
Text classification is critical for document and email categorization, document parsing, language detection, fraud and spam detection, sentiment analysis and more. While most data scientists and researchers are extremely comfortable building predictive models for structured data, when it comes to text data, they shun it for good reason. You don’t have a fixed number of features to work with, you are working in a very high dimensional space and words can always be expressed in a multitude of ways. In this hands-on class, we will teach you how to work with text data in order to build high accuracy text classification models.
Who will benefit from this course?
- Software Engineers
- Data Scientists
- Data Analysts
- Electrical/Mechanical/Biomedical Engineers
- Research Scientists
What you will learn?
By the end of this course, students will be able to:
- Choose the right models for text classification problems
- Perform appropriate feature engineering for text prediction tasks
- Build a text-classifier from scratch
- Evaluate the performance of text classifiers adequately
- Improve the accuracy of text classifiers
- Generalize text classification models for production use cases
- Hands-on with a mix of theory
- Basic knowledge in Machine Learning and Data Science
- Programming knowledge in Python
- 1-2 Full Days