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Difference between NLP, NLU and NLG
Importing NLTK library for NLP
Sentiment Analysis, Text Classification, Topic Modeling ,andText Summarization
Understanding Tokenization and Bag of Words
What do Ngram means and its significance
Difference between Lemmatization and Stemming
Part of Speech(POS) tagging
What are Stopwords and its use in the context of NLP
What are TFIDF vector and its significance
Binary Text classification and Text classification
Applying NLP pre-processing for training model
Applying LinearSVC for binary classification
Applying OneVsRestClassifier for Multi-Label Classification
Applying MultiLabelBinarizer for Multi-Label Classification
Understanding the evaluation metrics used for NLP(Precision, F1-score, Recall)
Evaluating the performance of the model and scope of improvement
Text cleaning and processing is an important task in every machine learning project where the task is to make sense of textual data. How to construct features from Text Data and further to it, create synthetic features are again critical tasks. On top of it how to apply machine learning models to create classifiers are also difficult.