What Will You Learn?
In this free NLP course, you'll learn the fundamentals of Natural Language Processing (NLP) and Python, covering data pre-processing, tokenization, stemming, lemmatization, and stopwords. Engage in hands-on sessions implementing these techniques in Python. Explore models like Bag of Words and TF-IDF, understand word embedding, delve into Machine Learning, logistic regression, and sentiment analysis, including a TextBlob demo. Conclude with insights into U-Net, semantic segmentation, and their demonstrations. Enroll, complete the quiz, and earn a certificate, taking a step towards mastering NLP. Explore Great Learning’s Best AI Courses for more on emerging technologies.
About This Course
Provider: Great Learning
Format: Online
Duration: 5 hours to complete [Approx]
Target Audience: Beginners
Learning Objectives: Upon completion, you will have mastered the fundamentals of Natural Language Processing (NLP) and Python, including data pre-processing, tokenization, stemming, lemmatization, stopwords handling, and hands-on implementation.
Course Prerequisites: NA
Assessment and Certification: Earn a Certificate upon completion from the relevant Provider
Instructor: Great Learning
Key Topics: Python Programming, Tokenization, Machine Learning and Logistic Regression, Natural Language Processing
Topic Covered:
- - What is NLP?
- - What is Python?
- - What is Data Pre-processing?
- - What is Tokenization?
- - What is Stemming?
- - What is Lemmatization?
- - What are Stopwords?
- - Modelling Techniques in NLP
- - What is Machine Learning and Logistic Regression?
- - What is Sentiment Analysis?
- - Demo on Sentiment Analysis
- - Course Outline for TextBlob
- - NLP Recap
- - Introduction to Textblob
- - Functionalities of Textblob
- - Textblob Sentiment Analysis
- - Introduction to U-Net
- - Introduction to Semantic Segmentation
- - Demo on Semantic Segmentation
0 Comments