Text Classification in NLP
The free course on Text Classification in NLP offers learners an opportunity to understand the fundamental concepts of Natural Language Processing (NLP) and how to classify text data using machine learning algorithms. Enroll Now!
What you learn in Text Classification in NLP ?
About this Free Certificate Course
Great Learning's free course on "Text Classification in NLP" is a comprehensive introduction to the field of Natural Language Processing (NLP) and machine learning-based text classification. The course is designed for beginners with no prior experience in NLP or machine learning.
The course covers the basics of text classification and explains how it works. Learners will gain a solid understanding of the techniques used in NLP for analyzing, processing, and categorizing text data. They will also learn how to evaluate the performance of a text classification model.
The course includes a Python walkthrough, where learners will learn how to implement text classification using popular machine learning algorithms such as Naïve Bayes, Linear Classifier, and Support Vector Classifier. The practical exercises and projects will help learners gain hands-on experience in text classification, making it easier for them to apply the concepts in real-world scenarios.
The course content is well-structured and easy to understand, with detailed explanations and examples provided throughout. Learners can work at their own pace, and the course is accessible from anywhere, making it a great option for busy professionals or students.
In conclusion, Great Learning's free course on "Text Classification in NLP" is an excellent resource for anyone interested in learning about NLP and machine learning-based text classification. With its comprehensive coverage of the subject and practical exercises, learners will gain valuable skills that they can apply in their professional or academic endeavors.
Course Outline
With this course, you get
Free lifetime access
Learn anytime, anywhere
Completion Certificate
Stand out to your professional network
1.5 Hours
of self-paced video lectures
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