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Natural Language Processing for Begineers

Instructor led best course for learning Natural language processing concepts and developing NLP models for text analytics.

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4.7

Rating

25 Hrs

Duration

Beginners

Level

20

Assignments

What you'll learn

Parts of speech tagging and text representation
Text preprocessing techniques including stemming and Lemmatization
Creating word embeddings for text classification, similarity and sentiment analysis

Who should take this course

Anyone with prior knowledge in python programming and Machine Learning
Anyone who wants to do analysis on unstructured text data

Skills you'll gain

POS tagging
Text representation
Text preprocessing
Word embeddings
Text similarity
Text classification
Text clustering
Opinion mining
Sentiment analysis

Course contents

Overview
Application of NLP
Python NLP libraries NLTK, Spacy

Understanding sentence structure
Word sense Disambiguation
Identifying entities and their relation

Bag of words
N gram

Different types of similarity measures

Text cleaning
Stop word removal
Stemming
Lemmatization

TF IDF
Word2Vec

Case study: categorizing news into groups

Topic mining
Case study: Customer feedback analysis

Sentiment analysis
Identifying aspects from topics
Case study: Customer feedback on iPhone product

Advanced NLP

Here Semantic embeddings, Information retrieval, Text summarization, Language modelling and recommendation engine concepts will be taught.

AI Agents for beginners

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LLM RAG for beginners

This course includes how to uses LLM and prompt engineering for question answering, reasoning, text summarization ect. Also allowing LLM to access knowledge from external sources using RAG.