Text Mining & Optical Character Recognition with Python (Learn the Basic Fundamentals of Text Mining)

Hi, and welcome to the Text Mining & Optical Character Recognition with Python course! If you aim to start with text analysis and document scanning in Python, this course is all you need. You will move from scratch and familiarise yourself with text mining and optical character recognition (OCR), focusing on understanding the concept, how it works, its utilization, and constraints. This course will then take you through a process of learning how to decode these techniques, even if you have never ventured into these topics before.

Regarding the practical assignments, the text mining part will allow you to work with actual projects, such as recognizing key entities in the news, classifying academic articles, and detecting sentiment in the articles on the products’ experience. We will introduce you to simple concepts like tokenization, filtering out the stop words, and methods of obtaining useful information from voluminous text inputs. After finishing this section, you could construct tools that could summarize a document, identify plagiarism, and classify spam mail.

In the OCR part, you will know one of the most important aspects of OCR: how to convert images and documents into texts for the purpose of data entry and analysis. Here, you will learn how OCR helps increase the efficiency of your data processing via projects such as Car License Plate Recognition, Handwritten Notes Recognition, and Receipt Recognition. This course, “Text Mining & Optical Character Recognition with Python,” combines the two categories of NLP, which are text mining and OCR, to equip you with the right tools required to develop applications that can contend with huge amounts of unstructured text and images.

Text Mining & Optical Character Recognition with Python Table of Contents:

1. Introduction - 06:56
2. Table of Contents - 07:22
3. Whom This Course is Intended For - 03:03
4. Tools, IDE, and Datasets - 08:52
5. Introduction to Text Mining - 06:51
6. Introduction to Optical Character Recognition - 07:01
7. Finding & Downloading Datasets From Kaggle - 03:57
8. Tokenization & Removing Stopwords with NLTK - 08:08
9. Stemming, Lemmatization, and Text Normalization with NLTK - 10:14
10. Building Named Entity Recognition System with Spacy & Flair - 08:40
11. Topic Modelling with Gensim & LDA - 16:32
12. News Articles Classification with TF-IDF - 24:36
13. Summarizing Text with Transformers & BART - 19:11
14. Extracting Keywords with Rake NLTK & Spacy - 10:58
15. Sentiment Analysis with TextBlob & BERT - 13:30
16. Building Plagiarism Detection Tool with TF-IDF & Cosine Similarity - 09:38
17. Building Spam Email Detection Tool with SVM - 20:53
18. Image Processing & Region of Interest Identification - 13:38
19. Building Car License Plate Recognition System with EasyOCR - 10:27
20. Building Handwriting Recognition System with EasyOCR - 07:33
21. Scanning Receipt with Tesseract - 10:52
22. Conclusion & Summary - 03:35

Who is this course for?

1. People who want to learn text mining
2. People who want to learn optical character recognition

Click on the links below to Download Text Mining & Optical Character Recognition with Python!