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Showing posts from October, 2024

Mastering NumPy: Your Comprehensive Course for Numerical Computing in Python

Comprehensive NumPy Course 📚 Comprehensive NumPy Course in Python Introduction to NumPy NumPy is a fundamental library for numerical computing in Python. It provides support for arrays, matrices, and a large number of mathematical functions to operate on these data structures. Installing NumPy You can install NumPy using pip: pip install numpy Key Functions in NumPy 1. Creating Arrays NumPy provides several functions to create arrays: np.array() : Creates an array from a list or tuple. np.zeros() : Creates an array filled with zeros. np.ones() : Creates an array filled with ones. np.arange() : Creates an array with a range of values. np.linspace() : Creates an array with evenly spaced values. Examples: import numpy as np # Creating an array from a l...

A Big Blast of Fun: The Elephant Toothpaste Experiment!

Elephant Toothpaste Experiment 🎉 Elephant Toothpaste Experiment! 🐘 What You Need: 1/2 cup of hydrogen peroxide (6% or 12% solution) 1 tablespoon of dish soap Food coloring (optional) 1 packet of dry yeast 3 tablespoons of warm water A clean plastic bottle Tray to catch the overflow Instructions: In a small bowl, mix the warm water and dry yeast. Let it sit for about 5 minutes. In the plastic bottle, combine the hydrogen peroxide, dish soap, and food coloring (if using). Pour the yeast mixture into the bottle and step back! Watch as a foamy eruption occurs, resembling a giant tube of toothpaste for elephants! What’s Happening? This experiment showcases a rapid decomposition reaction where hydrogen peroxide breaks down into water a...

History of Indian Railway Toilets

 History of I.Railway(1909) āϟ্āϰেāύ āĻāϏে āĻĻাঁ⧜াāϞো āĻŦীāϰāĻ­ূāĻŽেāϰ āφāĻšāĻŽেāĻĻāĻĒুāϰ āϏ্āϟেāĻļāύে।  āĻāĻ• āĻ­āĻĻ্āϰāϞোāĻ• āĻĒ্āϰāĻ•ৃāϤিāϰ āĻĄাāĻ•ে āϏা⧜া āĻĻিāϤে āϟ্āϰেāύ āĻĨেāĻ•ে āύেāĻŽে āϏ্āϟেāĻļāύāϏংāϞāĻ—্āύ āĻļৌāϚাāϞ⧟েāϰ āĻĻিāĻ•ে āĻ—েāϞেāύ। āĻļৌāϚাāϞ⧟ে āĻĨাāĻ•াāϰ āϏāĻŽā§Ÿেāχ āϤিāύি āϟ্āϰেāύ āĻ›ে⧜ে āĻĻেāĻ“ā§Ÿাāϰ āĻšুāχāϏāϞ āĻļুāύāϤে āĻĒাāύ। āĻ•োāύāϰāĻ•āĻŽে āϏেāĻ–াāύ āĻĨেāĻ•ে āĻŦেāϰি⧟ে āĻ›ুāϟāϞেāύ āϟ্āϰেāύ āϧāϰāϤে। āϟ্āϰেāύ āĻĨাāĻŽাāύোāϰ āϜāύ্āϝ āĻšাāϤ āϤুāϞে āϟ্āϰেāύেāϰ āĻ—াāϰ্āĻĄāĻ•ে āχāĻļাāϰা āĻ•āϰেāύ। āĻāĻ•āĻšাāϤে āϞোāϟা, āĻ…āύ্āϝāĻšাāϤে āϧুāϤি āϏাāĻŽāϞে āĻ›ুāϟāϤে āĻ—ি⧟ে āĻšুāĻŽā§œি āĻ–ে⧟ে āĻĒ⧜āϞেāύ āϞোāĻ•āĻ­āϰ্āϤি āĻĒ্āϞ্āϝাāϟāĻĢāϰ্āĻŽেāϰ āĻ“āĻĒāϰ। āϚোāĻ–েāϰ āϏাāĻŽāύে āĻĻি⧟ে āϟ্āϰেāύ āĻŦে⧜ি⧟ে āĻ—েāϞ। āĻ•্āώুāĻŦ্āϧ, āĻ…āĻĒāĻŽাāύিāϤ āĻ­āĻĻ্āϰāϞোāĻ• āϏ্āϟেāĻļāύ āϤ্āϝাāĻ— āĻ•āϰāϞেāύ।    āĻ•ā§ŸেāĻ•āĻĻিāύ āĻĒāϰ āĻŦিāϏ্āϤাāϰিāϤ āϘāϟāύা āϜাāύি⧟ে āϤিāύি āϚিāĻ ি āϞিāĻ–āϞেāύ āϏাāĻšেāĻŦāĻ—āĻž্āϜ āĻĄিāĻ­িāĻļāύাāϞ āϰেāϞāĻ“ā§Ÿে āĻ…āĻĢিāϏে। āϚিāĻ িāϤে āϤিāύি āϞেāĻ–েāύ, āĻĒেāϟāĻ­āϰে āĻ•াঁāĻ াāϞ āĻ–ে⧟ে āϟ্āϰেāύে āϚেāĻĒে āϝাāĻ“ā§Ÿাāϰ āϏāĻŽā§Ÿ āĻĒেāϟ āĻĢেঁāĻĒে āĻ“āĻ া⧟ āϤিāύি āĻŦাāϧ্āϝ āĻšā§Ÿে āϏ্āϟেāĻļāύেāϰ āĻļৌāϚাāϞ⧟ে āϝাāύ। āϤিāύি āĻĒ্āϰāĻļ্āύ āĻ•āϰেāύ, āĻšাāϤ āĻĻেāĻ–াāύো āϏāϤ্āĻŦেāĻ“ āĻ—াāϰ্āĻĄ āĻ•ি āĻĻু'-āĻāĻ• āĻŽিāύিāϟেāϰ āϜāύ্āϝ āϟ্āϰেāύāϟাāĻ•ে āĻĻাঁ⧜ āĻ•āϰাāϤে āĻĒাāϰāϤেāύ āύা ? āĻāĻŽāύāĻ•ি āϜāύāϏ্āĻŦাāϰ্āĻĨে āĻ“āχ āĻ—াāϰ্āĻĄেāϰ āĻ•াāĻ› āĻĨেāĻ•ে āĻŦ⧜āϏ⧜ āϜāϰিāĻŽাāύা āφāĻĻা⧟েāϰ āĻ•āĻĨাāĻ“ āĻŦāϞেāύ, āύা āĻšāϞে āϏংāĻŦাāĻĻāĻĒāϤ্āϰে āϏāĻŦāĻ•āĻĨা āĻĢাঁāϏ āĻ•āϰে āĻĻেāĻ“ā§Ÿাāϰ āĻšুāĻŽāĻ•ি āĻĻেāύ। āχংāϰেāϜি āĻŦ্āϝাāĻ•āϰāĻŖāĻ—āϤ āĻ­ুāϞে āϞেāĻ–া āϚিāĻ িāϟি āĻ¤ā§ŽāĻ•াāϞীāύ āĻŦ্āϰিāϟিāĻļ āϏāϰāĻ•াāϰ āϝāĻĨেāώ্āϟ āĻ—ুāϰুāϤ্āĻŦāϏāĻšāĻ•াāϰে...