Collect Data. Extract Data from PDF. PDF to Excel

πŸ‘‰  Collect Data. Extract Data from PDF. PDF to Excel | Udemy NED

 Collect Data. Extract Data from PDF. PDF to Excel Convert PDF documents to Text and Graphics. Data Visualisation. Python OCR. Practical Step-by-Step Course for Beginners.

 What you'll learn
  • How to convert a PDF to text?
  • How do I install Python?
  • How do you visualize a dataset?
  • What is GitHub and how do you use it?
  • What is regular expression?
  • How do I install VS Code?
  • How to run Python in VS Code?
  • How do you use kaggle dataset?
  • How to install pandas on Python?
  • How do I convert a PDF to TXT in Python?
  • What is the best Python IDE for beginners?
  • How can I iterate over files in a given directory?
  • How to Install Apache Tika on Windows?
  • How to split a string into a list?
  • How do I remove blank strings from a list?
  • How does Python interpreter choose VS code? 

This course is intended to be an initiation to learn #BigData and #MachineLearning with #Python programming for absolute beginners that have no background in programming.

In this course, we will step by step, using the example of real data, we will go through the main processes related to the topic "Big data and machine learning".  Since the material turned out to be voluminous, I divided the course into five parts.

This part - the first part is devoted to the collection and extraction of data from documents. In this course, you will learn how to extract data from PDF documents, drawings and any other documents in PDF format.

⇉ We will work on real data. We will have two sets of data consisting of PDF files that we will transform to the text and to tabular form. We will visualize the received data on the Kaggle platform using python libraries, which will help us to depict our received data in a graphical format.

⇉ During the training process, we will install Python and such libraries as Pandas, seaborn, matplotlib and others. We will upload the received data to the Kaggle platform and here using the “Jupiter Notebook” we will visualize our data and at the end, we will upload our data to the GitHub platform.

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