Unlock the Power of Text Mining & Optical Character Recognition with Python

Transform unstructured text data into valuable insights with our comprehensive project-based course on Text Mining & Optical Character Recognition with Python. Learn step-by-step how to perform advanced text mining techniques using natural language processing and build an optical character recognition system using EasyOCR and Tesseract.

This course perfectly combines text mining with computer vision, providing an ideal opportunity to practice your programming skills by building complex projects with real-world applications. You'll learn the basic fundamentals of text mining and optical character recognition, including their use cases, technical challenges, and limitations.

With this course, you'll gain the skills needed to develop advanced data-driven applications, ultimately enhancing your ability to solve complex real-world problems through data science and artificial intelligence.

Course Highlights

• Text Mining Fundamentals: Learn the basic fundamentals of text mining and its use cases, including data collection, text preprocessing, feature extraction, text analysis, and modeling.
• Optical Character Recognition Fundamentals: Learn the basic fundamentals of optical character recognition and its use cases, including image processing, region of interest identification, and text localization.
• Named Entity Recognition: Learn how to build named entity recognition systems using Spacy and Flair.
• Topic Modeling: Learn how to perform topic modeling using Gensim and LDA.
• Text Summarization: Learn how to build text summarizers using Transformers and BART.
• Keyword Extraction: Learn how to extract keywords using Rake NLTK and Spacy.
• Sentiment Analysis: Learn how to perform sentiment analysis using TextBlob and BERT.
• Plagiarism Detection: Learn how to build plagiarism detection tools using TF-IDF & Cosine Similarity.
• Spam Email Detection: Learn how to build spam email detection tools using support vector machines.
• Image Processing: Learn how to do image processing and identify region of interest.
• Car License Plate Recognition: Learn how to build car license plate recognition systems using EasyOCR.
• Handwriting Recognition: Learn how to build handwriting recognition systems using EasyOCR.
• Receipt Scanner System: Learn how to build receipt scanner systems using Tesseract.

Additional Projects

• Performing Sentiment Analysis on Client Feedback Using VADER: This project will teach you how to analyze client feedback using VADER, a sentiment analysis tool. You'll learn how to categorize feedback as positive, negative, or neutral to gain insights into client satisfaction and improve business strategies.
• Build Language Detection Model Using Naive Bayes: In this project, you'll build a language detection model using Naive Bayes, a popular machine learning algorithm. You'll train the model to accurately identify the language of text data, helping businesses and applications process multilingual content efficiently.
• OCR Extracting Text from Lab Report Image Using Pytesseract: This project guides you through extracting text from images, specifically lab reports, using Pytesseract, an OCR (Optical Character Recognition) tool. You'll learn how to automate text extraction from scanned or photographed documents for easy data analysis and processing.