NLP Boot-camp: Hands-on Text mining in Python using TextBlob

Text Mining, Natural Language Processing, Sentiment Analysis, and Classification for ABSOLUTE BEGINNERS in Python.

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NLP Boot-camp: Hands-on Text mining in Python using TextBlob

What You Will Learn!

Strong concepts regarding Natural Language processing
Complete command over Tokenization, Tagging and Noun Phrase Extraction
Complete knowledge regarding Sentiment Analysis, Words Inflection and lemmatization
Fully familiar with N-grams, Frequency and Text Classification System
Complete knowledge regarding Naive Bayes Classifiers and Model Accuracy
Complete knowledge regarding Language Detection, Translation, Spell Checking
In addition, student will learn "How to use NLTK classes in TextBlob?"

Description

In NLP Boot-camp: Hands-on Text mining in Python using TextBlob for Beginners course, you will learn Text Mining, Sentiment Analysis, Tokenization, Noun Phrase Extraction, N-grams, and so many new things. I will start from a very basic level where I will assume that everyone is an absolute beginner, having no knowledge regarding Machine Learning, Artificial Intelligence, and Natural Language Processing. So, I will be explaining everything in a very easy manner. I will start with Tokenization, Parts-of-speech tagging, Noun Phrase Extraction, Sentiment Analysis, Spell Checking, Words Inflection, Lemmatization, Spell Checking, Words, and Noun Phrase Frequency, and N-grams. Then, I will jump to the intermediate level where I will explain how to develop your own Text Classification System and I will explain what is Naive Bayes Classifier, how to create a model, its training and testing. In the advanced/ final level, I will explain Model Accuracy, then I will again explain about Tokenizer, Sentiment Analyzer, Parts-of-speech Tagger, and Noun Phrase Extractor. For all these projects, I will use one of the easiest Python libraries for Natural Language Processing and that is TextBlob. This NLP Boot-camp: Hands-on Text mining in Python using TextBlob for Beginners course is designed in such a way that after this course, learning other advanced Natural Language Processing Libraries like NLTK, Tensor-Flow, and Keras, etc will be no more difficult for you.