Text Mining & Optical Character Recognition with Python
Topic modelling, news classification, NER, sentiment analysis, keyword extraction, license plate recognition system
4.20 (10 reviews)
4 044
students
4.5 hours
content
Feb 2025
last update
$13.99
regular price
What you will learn
Learn the basic fundamentals of text mining and its use cases
Learn the basic fundamentals of optical character recognition and its use cases
Learn how text mining works. This section covers data collection, text preprocessing, feature extraction, text analysis and modeling
Learn how optical character recognition works. This section covers image preprocessing, text localization, character segmentation, character recognition
Learn how to do tokenization and remove stopwords using NLTK
Learn how to perform stemming, lemmatization, and text localization using NLTK
Learn how to build named entity recognition system using Spacy and Flair
Learn how to perform topic modeling using Gensim and LDA
Learn how to build news article classification using TF-IDF
Learn how to build text summarizer using Transformers and BART
Learn how to extract keywords using Rake NLTK and Spacy
Learn how to perform sentiment analysis using TextBlob and BERT
Learn how to build plagiarism detection tool using TF-IDF & Cosine Similarity
Learn how to build spam email detection tool using support vector machine
Learn how to do image processing and identify region of interest
Learn how to build car license plate recognition system using EasyOCR
Learn how to build handwriting recognition system using EasyOCR
Learn how to build receipt scanner system using Tesseract
Learn how to perform sentiment analysis on client feedback using VADER
Learn how to build language detection model using Naive Bayes
Learn how to extract text from lab report using Pytesseract
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6016464
udemy ID
10/06/2024
course created date
30/06/2024
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