Python Projects & Free Books
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Python Interview Projects & Free Courses

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๐Ÿฒ ๐—™๐—ฅ๐—˜๐—˜ ๐—ข๐—ป๐—น๐—ถ๐—ป๐—ฒ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ง๐—ผ ๐—–๐—ต๐—ฎ๐—ป๐—ด๐—ฒ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—–๐—ฎ๐—ฟ๐—ฒ๐—ฒ๐—ฟ ๐—œ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ ๐Ÿ˜

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๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/4e1I17a

๐Ÿ’ฅ Start learning today and build the skills top companies want!โœ…๏ธ
Must Know Fine Tuning Terms In LLM
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Forwarded from Artificial Intelligence
๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ณ๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜ ๐˜„๐—ถ๐˜๐—ต ๐—›๐—ฎ๐—ฟ๐˜ƒ๐—ฎ๐—ฟ๐—ฑ ๐—จ๐—ป๐—ถ๐˜ƒ๐—ฒ๐—ฟ๐˜€๐—ถ๐˜๐˜†๐Ÿ˜

๐ŸŽฏ Want to break into Data Science without spending a single rupee?๐Ÿ’ฐ

Harvard University is offering a goldmine of free courses that make top-tier education accessible to anyone, anywhere๐Ÿ‘จโ€๐Ÿ’ปโœจ๏ธ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/3HxOgTW

These courses are designed by Ivy League experts and are trusted by thousands globallyโœ…๏ธ
Loops in Python ๐Ÿ‘†
๐ˆ๐๐Œ ๐…๐‘๐„๐„ ๐‚๐ž๐ซ๐ญ๐ข๐Ÿ๐ข๐œ๐š๐ญ๐ข๐จ๐ง ๐‚๐จ๐ฎ๐ซ๐ฌ๐ž๐ฌ๐Ÿ˜

๐Ÿš€ Dive into the world of Data Analytics with these 6 free courses by IBM!

Gain practical knowledge and stand out in your career with tools designed for real-world applications.

All courses come with expert guidance and are free to access!๐ŸŽ‰

๐‹๐ข๐ง๐ค ๐Ÿ‘‡:- 
 
https://bit.ly/4iXOmmb
 
Enroll For FREE & Get Certified ๐ŸŽ“
๐Ÿ”— Master 8 Essential Machine Learning Algorithms
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๐Ÿฐ ๐—›๐—ถ๐—ด๐—ต-๐—œ๐—บ๐—ฝ๐—ฎ๐—ฐ๐˜ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐˜๐—ผ ๐—Ÿ๐—ฎ๐˜‚๐—ป๐—ฐ๐—ต ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—–๐—ฎ๐—ฟ๐—ฒ๐—ฒ๐—ฟ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ๐Ÿ˜

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Time Complexity of 10 Most Popular ML Algorithms
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When selecting a machine learning model, understanding its time complexity is crucial for efficient processing, especially with large datasets.

For instance,
1๏ธโƒฃ Linear Regression (OLS) is computationally expensive due to matrix multiplication, making it less suitable for big data applications.

2๏ธโƒฃ Logistic Regression with Stochastic Gradient Descent (SGD) offers faster training times by updating parameters iteratively.

3๏ธโƒฃ Decision Trees and Random Forests are efficient for training but can be slower for prediction due to traversing the tree structure.

4๏ธโƒฃ K-Nearest Neighbours is simple but can become slow with large datasets due to distance calculations.

5๏ธโƒฃ Naive Bayes is fast and scalable, making it suitable for large datasets with high-dimensional features.
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๐Ÿญ๐Ÿฌ๐Ÿฌ๐Ÿฌ+ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฒ๐—ฑ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ฏ๐˜† ๐—œ๐—ป๐—ณ๐—ผ๐˜€๐˜†๐˜€ โ€“ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป, ๐—š๐—ฟ๐—ผ๐˜„, ๐—ฆ๐˜‚๐—ฐ๐—ฐ๐—ฒ๐—ฒ๐—ฑ!๐Ÿ˜

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Python Full Stack Developer Roadmap:

Stage 1: HTML โ€“ Learn webpage basics.

Stage 2: CSS โ€“ Style web pages.

Stage 3: JavaScript โ€“ Add interactivity.

Stage 4: Git + GitHub โ€“ Manage code versions.

Stage 5: Frontend Project โ€“ Build a simple project.

Stage 6: Python (Core + OOP) โ€“ Learn Python fundamentals.

Stage 7: Backend Project โ€“ Use Flask/Django for backend.

Stage 8: Frameworks โ€“ Master Flask/Django features.
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