Machine Learning with Python
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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
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This GitHub repo is a gold mine for EVERY data scientist!

(full of hands-on and interactive tutorials)

DS Interactive Python provides several dashboards to interactively learn about statistics, ML models, and other related theoretical concepts!

Some key topics you can understand interactively:
โ€ข PCA
โ€ข Bagging and boosting
โ€ข Linear regression and OLS
โ€ข Bayesian and frequentist statistics
โ€ข confidence intervals
โ€ข clustering (kmeans, spectral clustering, etc.)
โ€ข central limit theorem
โ€ข neural networks (the backpropagation animation is really good)
โ€ข and many more.

Link: https://github.com/GeostatsGuy/DataScienceInteractivePython

https://t.iss.one/CodeProgrammer
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Create a Wi-Fi QR code in Python in a couple of seconds

pip install wifi_qrcode_generator


import wifi_qrcode_generator.generator
from PIL import Image

ssid = "CLCoding_WIFI"
password = "supersecret123"
security = "WPA"

from wifi_qrcode_generator.generator import wifi_qrcode
qr = wifi_qrcode(ssid, False, security, password)

qr.make_image().save("wifi_qr.png")
Image.open("wifi_qr.png")


๐Ÿ‘‰  @codeprogrammer
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Channel photo updated
Learn Complete MatPlotLib.pdf
4.3 MB
Learn Complete #MatPlotLib with most asked #interview questions

๐Ÿ‘‰  @codeprogrammer
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Amazing NumPy Cheat Sheet.pdf
259.7 KB
Amazing NumPy Cheat Sheet Snippet with 100 exercises for practicing the concept to get hands on to clear the coding round in the interviews

#NumPy #codingexams

https://t.iss.one/CodeProgrammer
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Machine Learning with Python
๐Ÿ’ธ PacketSDK--A New Way To Make Revenue From Your Apps Regardless of whether your app is on desktop, mobile, TV, or Unity platforms, no matter which app monetization tools youโ€™re using, PacketSDK can bring you additional revenue! โ— Working Principle: Convertโ€ฆ
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All Cheat Sheets Collection (3).pdf
2.7 MB
Python For Data Science Cheat Sheet

#python #datascience #DataAnalysis

https://t.iss.one/CodeProgrammer

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๐Ÿš€ ๐„๐ฉ๐จ๐œ๐ก ๐ฏ๐ฌ ๐ˆ๐ญ๐ž๐ซ๐š๐ญ๐ข๐จ๐ง ๐ข๐ง ๐ƒ๐ž๐ž๐ฉ ๐‹๐ž๐š๐ซ๐ง๐ข๐ง๐  โ€“ ๐“๐ก๐ž ๐Œ๐จ๐ฌ๐ญ ๐‚๐จ๐ฆ๐ฆ๐จ๐ง๐ฅ๐ฒ ๐‚๐จ๐ง๐Ÿ๐ฎ๐ฌ๐ž๐ ๐“๐ž๐ซ๐ฆ๐ฌ!

When training a neural network, two words confuse most beginners:

๐Ÿ”น ๐„๐ฉ๐จ๐œ๐ก
๐˜ˆ๐˜ฏ ๐˜ฆ๐˜ฑ๐˜ฐ๐˜ค๐˜ฉ ๐˜ฎ๐˜ฆ๐˜ข๐˜ฏ๐˜ด ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฎ๐˜ฐ๐˜ฅ๐˜ฆ๐˜ญ ๐˜ฉ๐˜ข๐˜ด ๐˜ด๐˜ฆ๐˜ฆ๐˜ฏ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฆ๐˜ฏ๐˜ต๐˜ช๐˜ณ๐˜ฆ ๐˜ฅ๐˜ข๐˜ต๐˜ข๐˜ด๐˜ฆ๐˜ต ๐˜ฐ๐˜ฏ๐˜ค๐˜ฆ.
๐˜๐˜ง ๐˜บ๐˜ฐ๐˜ถ ๐˜ต๐˜ณ๐˜ข๐˜ช๐˜ฏ ๐˜ง๐˜ฐ๐˜ณ 10 ๐˜ฆ๐˜ฑ๐˜ฐ๐˜ค๐˜ฉ๐˜ด, ๐˜บ๐˜ฐ๐˜ถ๐˜ณ ๐˜ฎ๐˜ฐ๐˜ฅ๐˜ฆ๐˜ญ ๐˜จ๐˜ฐ๐˜ฆ๐˜ด ๐˜ต๐˜ฉ๐˜ณ๐˜ฐ๐˜ถ๐˜จ๐˜ฉ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ธ๐˜ฉ๐˜ฐ๐˜ญ๐˜ฆ ๐˜ฅ๐˜ข๐˜ต๐˜ข 10 ๐˜ต๐˜ช๐˜ฎ๐˜ฆ๐˜ด.

๐Ÿ”น ๐ˆ๐ญ๐ž๐ซ๐š๐ญ๐ข๐จ๐ง
๐˜ˆ๐˜ฏ ๐˜ช๐˜ต๐˜ฆ๐˜ณ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ ๐˜ช๐˜ด ๐˜ฐ๐˜ฏ๐˜ฆ ๐˜ธ๐˜ฆ๐˜ช๐˜จ๐˜ฉ๐˜ต ๐˜ถ๐˜ฑ๐˜ฅ๐˜ข๐˜ต๐˜ฆ, ๐˜ฃ๐˜ข๐˜ด๐˜ฆ๐˜ฅ ๐˜ฐ๐˜ฏ ๐˜ข ๐˜ด๐˜ช๐˜ฏ๐˜จ๐˜ญ๐˜ฆ ๐˜ฃ๐˜ข๐˜ต๐˜ค๐˜ฉ ๐˜ฐ๐˜ง ๐˜ฅ๐˜ข๐˜ต๐˜ข.

If you have:
10,000 ๐˜ณ๐˜ฆ๐˜ค๐˜ฐ๐˜ณ๐˜ฅ๐˜ด
๐˜‰๐˜ข๐˜ต๐˜ค๐˜ฉ ๐˜ด๐˜ช๐˜ป๐˜ฆ = 100
๐Ÿ‘‰ ๐˜›๐˜ฉ๐˜ฆ๐˜ฏ ๐˜บ๐˜ฐ๐˜ถ ๐˜จ๐˜ฆ๐˜ต 100 ๐˜ช๐˜ต๐˜ฆ๐˜ณ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ๐˜ด ๐˜ฑ๐˜ฆ๐˜ณ ๐˜ฆ๐˜ฑ๐˜ฐ๐˜ค๐˜ฉ.

โœ”๏ธ ๐’๐ข๐ฆ๐ฉ๐ฅ๐ž ๐€๐ง๐š๐ฅ๐จ๐ ๐ฒ
๐“๐ก๐ข๐ง๐ค ๐จ๐Ÿ ๐ ๐จ๐ข๐ง๐  ๐ญ๐จ ๐ญ๐ก๐ž ๐ ๐ฒ๐ฆ:
๐„๐ฉ๐จ๐œ๐ก = ๐œ๐จ๐ฆ๐ฉ๐ฅ๐ž๐ญ๐ข๐ง๐  ๐ญ๐ก๐ž ๐ž๐ง๐ญ๐ข๐ซ๐ž ๐ฐ๐จ๐ซ๐ค๐จ๐ฎ๐ญ ๐ฉ๐ฅ๐š๐ง ๐จ๐ง๐œ๐ž
๐ˆ๐ญ๐ž๐ซ๐š๐ญ๐ข๐จ๐ง = ๐๐จ๐ข๐ง๐  ๐จ๐ง๐ž ๐ฌ๐ž๐ญ ๐ข๐ง๐ฌ๐ข๐๐ž ๐ญ๐ก๐š๐ญ ๐ฐ๐จ๐ซ๐ค๐จ๐ฎ๐ญ

The model becomes stronger with every iteration, and improves overall with more epochs.


Read More: https://telegra.ph/Demystifying-Epochs--Iterations-in-Deep-Learning-11-24

๐Ÿ‘‰  @codeprogrammer
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Statistics for Data Science Notes.pdf
2.1 MB
๐Ÿท "Statistics for Data Science" Notes


๐Ÿ‘จ๐Ÿปโ€๐Ÿ’ป In these notes, everything is structured and neatly organized from the basics of statistics to advanced tips. Each concept is explained with examples, formulas, and charts to make learning easy

๐Ÿ›‘ What is statistics and why is it important?
๐Ÿ›‘ Basic concepts
๐Ÿ›‘ Descriptive statistics
๐Ÿ›‘ Inferential statistics
๐Ÿ›‘ Discrete and continuous distributions
๐Ÿ›‘ And many other topics

๐ŸŒ #Data_Science #DataScience

https://t.iss.one/CodeProgrammer โœ…

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Forwarded from Data Analytics
pandas Cheat Sheet.pdf
1.6 MB
๐Ÿ“• #pandas Cheat Sheet


๐Ÿ‘จ๐Ÿปโ€๐Ÿ’ป To easily read, inspect, clean, and manipulate data however you want, you need to master pandas!

โœ๏ธ To make learning and using pandas easier, this #cheatsheet covers almost all the important features you need for data-driven projects.

โœ”๏ธ Reading and writing data
โœ”๏ธ Data inspection
โœ”๏ธ Data transformation and cleaning
โœ”๏ธ Grouping and summarizing
โœ”๏ธ Combining datasets

๐ŸŒ #DataScience #DataScience

https://t.iss.one/DataAnalyticsX ๐Ÿ
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Data Analytics
pandas Cheat Sheet.pdf
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๐Ÿš€ Master Data Science & Programming!

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๐Ÿ”– Machine Learning
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๐ŸŽง Learn Python Hub
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Admin: @HusseinSheikho
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