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علوم داده و یادگیری ماشین: به عنوان مثال، پایتون با کتابخانه‌های متعددی مثل NumPy، Pandas و Scikit-learn یک ابزار قدرتمند برای تحلیل داده‌ها و مدل‌سازی هوش مصنوعی است.
توسعه وب: با استفاده از فریم‌ورک‌هایی مانند Django و Flask، توسعه‌دهندگان می‌توانند به‌سادگی برنامه‌های وب مقیاس‌پذیر و حرفه‌ای بسازند.
خودکارسازی و اسکریپت‌نویسی: از پایتون برای نوشتن اسکریپت‌های خودکارسازی وظایف تکراری یا پیچیده استفاده می‌شود.

توسعه بازی: با کتابخانه Pygame، می‌توان بازی‌های ساده‌ای را توسعه داد.

امنیت سایبری و تست نفوذ: پایتون به عنوان ابزار قدرتمندی برای تست نفوذ و خودکارسازی فرآیندهای امنیت سایبری شناخته می‌شود.

python_developer
کاربردهای پایتون:

علوم داده و یادگیری ماشین: به عنوان مثال، پایتون با کتابخانه‌های متعددی مثل NumPy، Pandas و Scikit-learn یک ابزار قدرتمند برای تحلیل داده‌ها و مدل‌سازی هوش مصنوعی است.
توسعه وب: با استفاده از فریم‌ورک‌هایی مانند Django و Flask، توسعه‌دهندگان می‌توانند به‌سادگی برنامه‌های وب مقیاس‌پذیر و حرفه‌ای بسازند.
خودکارسازی و اسکریپت‌نویسی: از پایتون برای نوشتن اسکریپت‌های خودکارسازی وظایف تکراری یا پیچیده استفاده می‌شود.

توسعه بازی: با کتابخانه Pygame، می‌توان بازی‌های ساده‌ای را توسعه داد.

امنیت سایبری و تست نفوذ: پایتون به عنوان ابزار قدرتمندی برای تست نفوذ و خودکارسازی فرآیندهای امنیت سایبری شناخته می‌شود.
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