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Text Classification in NLP

star 4.59  Beginner level 2.25 learning hrs 2.6K+ Learners

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!

Instructor:

Ms. Sowmya Vivek

Key Highlights

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About this 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.
 

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Course outline

Introduction to Text Classification

How does text classification work ?

Python walkthrough - Text classification-Naïve Bayes, Linear classifier, Support vector classifier

Get access to the complete curriculum once you enroll in the course

Text Classification in NLP

rating icon 4.59

2.25 Hours

Beginner

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2.6K+ learners enrolled so far

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Master in-demand skills & tools

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Learner reviews of the Free Courses

4.59
72%
22%
5%
1%
0%
Reviewer Profile

5.0

Country Flag India
“Fundamentals of Text Classification”
Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that deals with the interaction between computers and humans in natural language. Key Aspects of NLP: 1. Text Processing: NLP involves processing and analyzing text data, including tokenization, stemming, and lemmatization. 2. Syntax and Semantics: NLP examines the structure and meaning of language, including grammar, syntax, and context. 3. Machine Learning: NLP employs machine learning algorithms to enable computers to learn from and improve their language understanding. 4. Applications: NLP has various applications, such as sentiment analysis, language translation, text summarization, and chatbots.
Reviewer Profile

5.0

Country Flag India
“Curriculum Skills and Tools: Topic Depth”
The course offered a solid introduction to text classification, covering essential topics like supervised and unsupervised learning, feature extraction, and common algorithms such as Naive Bayes and SVM. The concepts were well explained, but it would have been beneficial to dive deeper into more advanced techniques like transformers or deep learning models, as they are highly relevant in modern NLP.
Reviewer Profile

4.0

Country Flag India
“Fundamentals of Text Classification in NLP”
The course is designed to introduce learners to the basics of text classification in Natural Language Processing (NLP), focusing on teaching concepts such as understanding text preprocessing techniques (tokenization, stop-word removal, stemming), utilizing machine learning algorithms like Naive Bayes, SVM, or deep learning approaches for text classification, and implementing sentiment analysis or spam detection as real-world applications.
Reviewer Profile

4.0

Country Flag India
“Mastering Fundamentals of Text Classification in NLP”
I found the Fundamentals of Text Classification in NLP course very insightful and well-structured. The instructors provided a solid theoretical foundation, followed by practical applications that helped me understand key concepts like tokenization, vectorization, and model evaluation. The hands-on exercises were particularly useful for reinforcing the learning.
Reviewer Profile

5.0

Country Flag India
“Valuable Insights into Text Classification”
I really enjoyed learning about the various aspects of text classification, especially distinguishing between rule-based and machine learning models. The practical examples, like sentiment analysis for customer feedback, helped solidify my understanding. The course content was well-organized and easy to follow, making complex concepts more approachable. The hands-on exercises also enhanced my ability to apply what I learned in real-world scenarios, such as identifying the challenges associated with using large corpora for ML models.
Reviewer Profile

5.0

Country Flag India
“Text Classification Certification: Skills to Categorize Text Data”
Text classification certification equips participants with skills to categorize text data. It covers topics like data preprocessing, feature extraction (e.g., TF-IDF), machine learning algorithms (e.g., Naive Bayes, SVM), and model evaluation techniques. The program includes hands-on projects to build and deploy models, enhancing expertise in NLP and machine learning for better job market competitiveness.
Reviewer Profile

5.0

Country Flag India
“Text Classification Certification: Skills to Categorize Text Data”
Text classification certification equips participants with skills to categorize text data. It covers topics like data preprocessing, feature extraction (e.g., TF-IDF), machine learning algorithms (e.g., Naive Bayes, SVM), and model evaluation techniques. The program includes hands-on projects to build and deploy models, enhancing expertise in NLP and machine learning for better job market competitiveness.
Reviewer Profile

5.0

Country Flag India
“Insightful Course on Fundamentals of Text Classification: A Comprehensive Journey!”
It sounds like you found the course on fundamentals of text classification to be insightful and comprehensive! Text classification is a key concept in Natural Language Processing (NLP), where the goal is to categorize text into predefined labels. The course likely covered essential topics such as introduction to text classification, understanding the basics of text categorization, rule-based and machine learning (ML)-based approaches, and types of text classification including sentiment analysis, spam detection, and topic labeling.
Reviewer Profile

5.0

Country Flag India
“Engaging and Informative Course with Practical Tools and Great Instructor”
I really enjoyed the Skills & Tools section, which provided me with practical, hands-on techniques that I can immediately apply to real-world scenarios. Additionally, the instructor was outstanding in explaining complex concepts in a clear and relatable way. Their enthusiasm and expertise made learning enjoyable and motivating. The course structure was also easy to follow, ensuring that I could progress at my own pace while grasping key concepts.
Reviewer Profile

5.0

Country Flag India
“This NLP Course is a Must for Anyone Looking to Build or Enhance Their Skills”
The course content is up-to-date, covering a wide range of topics from basic text processing to advanced techniques like transformer models and sentiment analysis. The real-world examples and projects provided valuable practical experience, helping me apply what I learned to real scenarios.

What our learners enjoyed the most

Our course instructor

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Ms. Sowmya Vivek

Independent Consultant, Visiting Faculty

Artificial Intelligence Expert

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8.3K+ Learners
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3 Courses
Sowmya is an Independent consultant working on projects on Customer Analytics, Deep Learning & NLP. She is a visiting faculty at Great Learning and a course Instructor at DataCamp USA. Sowmya has 25 years of experience spread across ML modelling, Business Intelligence, Workflow optimisation, Content Management & e-learning content development.

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