Professional Trader
NLP for Text Processing
Overview
Master Natural Language Processing techniques to analyze, process, and interpret text data using Python and deep learning frameworks.
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35 Hours of Learning
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0.9K+ Learners
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55,000+ GST
Skills You Will Learn
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Python NLP coding
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Deep learning for text
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Building chatbots
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Using word embeddings
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Model fine-tuning
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Transfer learning for NLP
Course Key Highlights
- Learn text preprocessing and tokenization techniques
- Implement NER and part-of-speech tagging models
- Build sentiment analysis and classification systems
- Work with Word2Vec, GloVe, and FastText embeddings
- Apply topic modeling with LDA and NMF methods
- Develop chatbot applications using deep learning
- Optimize NLP models via transfer learning
Course Time
Includes:
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Self-paced
Modules -
Case studies
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Quizzes & assessments
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35 Hours of Learning
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Leverage NLP and deep learning to extract insights from text data and build AI-driven trading tools.
Key Highlights:
- Fundamentals of NLP, text preprocessing, tokenization
- NER, POS tagging & language parsing
- Sentiment analysis & classification models
- Word embeddings: Word2Vec, GloVe, FastText
- Topic modeling with LDA and NMF
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FAQs
What programming language will be used in this course?
The course uses Python for implementing NLP techniques and models.
Does the course include deep learning-based NLP methods?
Yes, you will learn to use deep learning frameworks for advanced NLP applications.
Will I work on practical projects during the course?
Yes, the course includes case studies and projects to apply your learning.
Does the course cover chatbot development?
Yes, building chatbot applications using NLP and deep learning is part of the curriculum.
Are topic modeling techniques included?
Yes, the course covers topic modeling methods like LDA and NMF.
