Python Developer Needed for Data Cleaning
Budget: ₹1,500 – ₹12,500 INR
I'm searching for a Python developer to help with a data cleaning project.
We are looking for an experienced OCR Text Cleaning and Processing Specialist to join our team on a freelance basis. The primary role involves cleaning and processing OCR output from digitized academic books, ensuring the text is accurate, structured, and ready for digital archiving and further use. Responsibilities:
Character Substitution: Correct common OCR mistakes
Paragraph Reconstruction: Ensure that lines are correctly grouped into paragraphs to match the original text structure.
Section Identification: Use patterns or other techniques to identify and separate headings and subheadings.
Table Handling: reconstruct tables from text data. Figure Handling: Ensure figure captions are correctly associated with their respective figures.
Consistent Formatting: Standardize the use of fonts, styles, and sizes across the text. Noise Removal: Eliminate non-text elements, noise, and artifacts from the OCR output.
Whitespace Normalization: Normalize whitespace to ensure uniformity throughout the document.
Spell Checking and Character Correction: Perform spell checks and correct character recognition errors. Quality Assurance: Implement and maintain a feedback loop for continuous process improvement.
We are looking for an experienced OCR Text Cleaning and Processing Specialist to join our team on a freelance basis. The primary role involves cleaning and processing OCR output from digitized academic books, ensuring the text is accurate, structured, and ready for digital archiving and further use. Responsibilities:
Character Substitution: Correct common OCR mistakes
Paragraph Reconstruction: Ensure that lines are correctly grouped into paragraphs to match the original text structure.
Section Identification: Use patterns or other techniques to identify and separate headings and subheadings.
Table Handling: reconstruct tables from text data. Figure Handling: Ensure figure captions are correctly associated with their respective figures.
Consistent Formatting: Standardize the use of fonts, styles, and sizes across the text. Noise Removal: Eliminate non-text elements, noise, and artifacts from the OCR output.
Whitespace Normalization: Normalize whitespace to ensure uniformity throughout the document.
Spell Checking and Character Correction: Perform spell checks and correct character recognition errors. Quality Assurance: Implement and maintain a feedback loop for continuous process improvement.