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Source channel @githubtrending · Post #15105 · Aug 30

#other This guide helps you prepare for software engineering technical interviews by covering key topics like good coding practices (SOLID principles, DRY, Clean Code, Clean Architecture), algorithms and data structures, design patterns, system design, databases, version control, CI/CD, containers, and AI tools. It offers practical resources and examples for many programming languages and frameworks, plus common interview questions for frontend and backend roles. Using this guide improves your coding skills, helps you understand important concepts, and boosts your confidence to perform well in interviews and real projects. It saves you time by gathering essential knowledge and practice materials in one place. https://github.com/DevCaress/guia-entrevistas-de-programacion

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djangoproject

@djangoproject · Post #507 · 11/26/2017, 10:08 PM

http://devarea.com/machine-learning-with-python-introduction/#.Whs6iCehU8o #Machine_Learning With Python – Introduction #Numpy is package for multi dimension arrays – very effective implementation #Scipy – package for scientific programming , mathematics , signal processing and more #Pandas – package for data handling #Matplotlib – package for data visualization (graphs) #Seaborn – extend Matplotlib with statistical graphs #Scikits – many extensions to spicy for specific fields like x-ray, image processing , deep learning and many more