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Step-by-Step Guide to Reading Different Files in Python

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 In the world of data science, automation, and general programming, working with files is unavoidable. Whether you’re dealing with CSV reports, JSON APIs, Excel sheets, or text logs, Python provides rich and easy-to-use libraries for reading different file formats. In this guide, we’ll explore how to read different files in Python , with code examples and best practices. 1. Reading Text Files ( .txt ) Text files are the simplest form of files. Python’s built-in open() function handles them effortlessly. Example: # Open and read a text file with open ( "sample.txt" , "r" ) as file: content = file.read() print (content) Explanation: "r" mode means read . with open() automatically closes the file when done. Best Practice: Always use with to handle files to avoid memory leaks. 2. Reading CSV Files ( .csv ) CSV files are widely used for storing tabular data. Python has a built-in csv module and a powerful pandas library. Using cs...
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The Growth of Machine Learning till TensorFlow

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The Internet and the vast amount of data are inspirations for CEOs of big corporations to start to use Machine learning. It is to provide a better experience to users. How TensorFlow Starts Let us take Amazon, online retail that uses Machine learning. The algorithm's purpose is to generate revenue. Based on user search data, the ML application provides information or insights. The other example is the advertising platform where Google is a leader in this line. Where it shows ads based on the user movements while surfing the web. These are just a few, but there are many in reality. Machine Learning Evolution Top ML Frameworks Torch The torch is the first framework developed in 2002 by Ronan Collobert. Initially, IBM and Facebook have shown much interest. The interface language is Lua. The primary focus is matrix calculations. It is suitable for developing neural networks. Theano It is developed in 2010 by the University of Montreal. It is highly reliable to process graphs (GPU). The...
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