Introduction to NLP and Text Mining
  • Introduction to Text Mining
  • Need for Preparation Before Text Mining
  • Getting Ready for Data Preparation
  • Reading Text Data as Corpus
  • Text Data Cleaning Stages
  • Tokenizing
  • Stop Words
  • Stemming and Lemmatizing
  • Final Cleaning using Regular Expressions
  • LAB_Data Cleaning Case Study on News Data
  • Document Term Matrix
  • LAB_ Document Term Matrix
  • NLP and Text Mining Basics Conclusion
Sentiment Analysis
  • Introduction to Sentiment Analysis
  • Sentiment Analysis Algorithms
  • LAB Case Study_ Importing Movies Review Data
  • LAB Case Study Creating DTM
  • LAB Case Study Refining DTM
  • Understanding Bayes Theorem P1
  • Understanding Bayes Theorem P2
  • Bayes Theorem to Naive Bayes Model
  • LAB Building and Validating Sentiment Analysis Model
  • Sentiment Analysis Conclusion
Document Categorisation
  • Introduction to Document Categorisation
  • Document categorisation using Naive Bays model
  • LAB Importing data and Preprocessing
  • LAB Preparing NLTK Friendly Feature Set
  • LAB Model Building and Exploring Results
  • LAB Multiple Document Categorisation
  • SVM Model for Text Classification
  • Understanding SVM Hyper Parameters to improve model
  • LAB Tuning SVM Hyper Parameters to Improve Model
  • Document Categorisation Conclusion