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A Beginner introduction to Natural Language Processing
Chapter Zero
An Introduction to NLP
Real Life Applications (3:56)
Demand Of NLP Experts (4:05)
Course Curriculum (2:04)
Introduction & Overview
Introduction & Overview (9:38)
Installation and Setup (13:20)
Installation and Setup Study Note
Applications (12:09)
Introduction to NLTK toolkit
Word and Sentence Tokenization (3:36)
Word and Sentence Tokenization : Study Note
POS Tagging (1:52)
POS Tagging Study Note
Named Entity Recognition [NER] (3:25)
Named Entity Recognition (NER) Study Note
Introduction to Machine Learning
NLP and Machine Learning (5:34)
What is Machine Learning (4:12)
What is Machine Learning Study Note
Types Of Machine Learning Problems Regression and Classification (9:39)
Types Of Machine Learning Problems Regression and Classification Study Note
Machine Learning for binary and multi class Classification
Bag Of Words (1:56)
Bag Of Words Study Note
Binary Classification & Multi Class Classification (8:20)
Binary Classification & Multi Class Classification Study Note
Introduction to word Embedding
One Hot Encoding (3:47)
One Hot Encoding Study Note
Count Vectorizer (13:35)
Count Vectorizer Study Note
Tfidf Vectorizer (8:48)
Hash Vectorizer (7:12)
Hash Vectorizer and Tf-Idf Vectorizer Study Note
Deep Neural Networks for Word Embedding – Word2Vec, GloVe
Wor2Vec Usage (5:10)
Wor2Vec Usage Study Note
Introduction to Neural Net (4:55)
Introduction to Neural Net Study Note
Activation Functions (3:49)
Activation Functions Study Notes
Document and Sentence Embedding
Document and Sentence Embedding (5:08)
Sentiment Analysis – Classical and Deep ML
Sentiment Analysis (6:53)
Named Entity Extraction – Classical and Deep ML
Named Entity Extraction (5:38)
Neural Machine Translation
Neural Machine Translation (9:57)
Project : Question Classification on NLP
Project : Question Classification on NLP (21:26)
Types Of Machine Learning Problems Regression and Classification Study Note
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