With a hands-on and interactive approach, we will understand essential concepts in NLP along with extensive case- studies and hands-on examples to master state-of-the-art tools, techniques and frameworks for actually applying NLP to solve real- world problems. We will leverage machine learning, deep learning and deep transfer learning to solve some popular tasks in NLP.
We will leverage machine learning, deep learning and deep transfer learning to solve some popular tasks in NLP including the following:
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Introduction to NLP
- Basics
- POS Tagging
- NER
- Text Wrangling
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Text Representation
- Traditional Statistical Models – BOW, TFIDF
- Embedding Models
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NLP Applications
- Text Similarity Content Recommenders
- Topic Modeling
- Text Summarization (Extractive)
- Text Classification (ML, DNN, CNN, LSTM, BERT)
- Multi-Task NLP (Transformers)