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Python Episode 2: Create Tools & Write Code in Termux (Beginner to Advanced) Description In this episode of Python Episode 2, you'll learn how to create real tools and write code directly on your Android phone using Termux. We start with the basics by using Nano to write your first Python script, then take it further by turning that script into a command-line tool. You'll learn how to add a shebang line, make scripts executable, create a tools directory, add it to your PATH, and run your tools f
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Python Episode 2: Create Tools & Write Code in Termux (Beginner to Advanced) Description In this episode of Python Episode 2, you'll learn how to create real tools and write code directly on your Android phone using Termux. We start with the basics by using Nano to write your first Python script, then take it further by turning that script into a command-line tool. You'll learn how to add a shebang line, make scripts executable, create a tools directory, add it to your PATH, and run your tools f
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Python explained in 30 seconds for beginners, and how to learn it step by step #coding #codingforbeginners #learntocode #python #computerscience
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Expresión Lógica en Python: Explicación Detallada y Ejemplos
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Python vs JavaScript: Which is more useful in 2026? 🐍⚡ The answer depends on what you’re building. 🐍 Python dominates AI, machine learning, data science, automation, and research. Its ecosystem includes tools like PyTorch, TensorFlow, NumPy, and pandas, making it the default choice for much of modern AI. ⚡ JavaScript is unavoidable for the web because it runs natively in browsers. With Node.js, it also powers backend applications, while frameworks like React Native extend it to mobile developm
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I’m wrapped up by a giant 16 foot Burmese python but it’s no big deal! #Python #Snake #Animals #Wildlife #learning
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Nobody ever wrote the code that lets ChatGPT write Python. Not one line of it. 🤯 Here's how a large language model actually gets built, step by step: 1️⃣ Data. Trillions of words of books, web pages, code and forums, then cleaned: duplicates removed, spam filtered, broken text stripped. One open dataset, FineWeb, is 15 trillion tokens of web text. 2️⃣ Tokens. The model never sees words.
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