
Explore text mining and natural language processing using text block, covering tokenization, parts of speech tagging, sentiment analysis, language detection, translation, and model training and evaluation.
Explore TextBlob, a Python library for processing textual data with simple APIs for natural language processing, including part of speech tagging, noun phrase extraction, sentiment analysis, classification, and translation.
Parts Of Speech Abbrivations:
CC coordinating conjunction
CD cardinal digit
DT determiner
EX existential there (like: “there is” … think of it like “there exists”)
FW foreign word
IN preposition/subordinating conjunction
JJ adjective ‘big’
JJR adjective, comparative ‘bigger’
JJS adjective, superlative ‘biggest’
LS list marker 1)
MD modal could, will
NN noun, singular ‘desk’
NNS noun plural ‘desks’
NNP proper noun, singular ‘Harrison’
NNPS proper noun, plural ‘Americans’
PDT predeterminer ‘all the kids’
POS possessive ending parent‘s
PRP personal pronoun I, he, she
PRP$ possessive pronoun my, his, hers
RB adverb very, silently,
RBR adverb, comparative better
RBS adverb, superlative best
RP particle give up
TO to go ‘to‘ the store.
UH interjection errrrrrrrm
VB verb, base form take
VBD verb, past tense took
VBG verb, gerund/present participle taking
VBN verb, past participle taken
VBP verb, sing. present, non-3d take
VBZ verb, 3rd person sing. present takes
WDT wh-determiner which
WP wh-pronoun who, what
WP$ possessive wh-pronoun whose
WRB wh-abverb where, when
Explore words inflection, the process of word formation, and learn how to convert words between singular and plural forms. Practice tokenizing sentences and applying pluralization and singularization functions to text.
learn to compute word and noun phrase frequencies in sentences using textblob in python, comparing dictionary-based counts with built-in count methods, including case sensitivity options.
Explore how TextBlob acts like a Python string, converting to uppercase, locating a word's position with zero-based indexing, and comparing strings for text mining tasks.
Classify text with a sentiment classifier, test model accuracy on positive and negative sentences, and examine probability outputs converted to percentages for clear interpretation.
Create a TextBlob object and apply a classifier to individual sentences to determine positive or negative sentiment, then compare sentence-level results with paragraph classification for clearer text analysis.
Check the model's accuracy with a test dataset, convert it to a percentage, and print the result to evaluate text classification, then update the model with data and re-check accuracy.
Explore sentiment analyzer in TextBlob, comparing the pattern-based and naive bayes analyzers trained on movie reviews, and learn to override the default analyzer for positive or negative classifications and scores.
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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.