PySpark - Create RDD from Text File
Resilient Distributed Datasets (RDDs) represent PySpark’s fundamental abstraction for distributed data processing. While DataFrames have become the preferred API for structured data, RDDs remain…
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NumPy - Save/Load as Text File (np.savetxt, np.loadtxt)
• np.savetxt() and np.loadtxt() provide straightforward text-based serialization for NumPy arrays with human-readable output and broad compatibility across platforms
Linux Text Processing with awk: Field Processing
awk operates on a simple but powerful data model: every line of input is automatically split into fields. This field-based approach makes awk exceptionally good at processing structured text like log…
Read more →Linux Text Processing with cut, sort, uniq, and wc
Linux text processing commands are the Swiss Army knife of data analysis. While modern tools like jq and Python scripts have their place, the classic utilities—cut, sort, uniq, and…
Linux Text Processing with grep: Pattern Searching
The grep command (Global Regular Expression Print) is one of the most frequently used utilities in Unix and Linux environments. It searches text files for lines matching a specified pattern and…
Linux Text Processing with sed: Stream Editor
• sed processes text as a stream, making it memory-efficient for files of any size and perfect for pipeline operations where you transform data on-the-fly without creating intermediate files
Read more →How to Use TEXT in Excel
The TEXT function in Excel transforms values into formatted text strings. The syntax is straightforward: =TEXT(value, format_text). The first argument is the value you want to format—a number,…
How to Implement Text Classification in PyTorch
Text classification is one of the most common NLP tasks in production systems. Whether you’re filtering spam emails, routing customer support tickets, analyzing product reviews, or categorizing news…
Read more →How to Implement Text Classification in TensorFlow
Text classification assigns predefined categories to text documents. Common applications include sentiment analysis (positive/negative reviews), spam detection (spam/not spam emails), and topic…
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