Coding Projects in Python (DK).pdf
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Coding projects in Python
DK, 2017
DK, 2017
Practical Python Dat... by Ashwin Pajankar.pdf
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Practical Python Data Visualization
Автор: Ashwin Pajankar
Автор: Ashwin Pajankar
https_coderbooks_ruIntroduction_to_Data_Science_Data_Analysis_and.pdf
73.6 MB
Introduction to Data Science
Автор: Rafael A. Irizarry
Автор: Rafael A. Irizarry
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ebook-seo-sej-complete-guide-2018.pdf
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Seo full guide pdf ☠️
React for more ❤️
React for more ❤️
Data Structure Book by Yandyesh.pdf
12 MB
Complete DSA Book 📕 with simple & point wise explanations - 159 Pages ❤️
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Python Data Stracture.pdf
4 MB
📖Data Structure Using Python 🔰
React ❤️🔥 for more
React ❤️🔥 for more
Python Pandas for Machine learning Notes.pdf
26 MB
Python Pandas for Machine learning Notes ❤️
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How Coders Can Survive—and Thrive—in a ChatGPT World
Artificial intelligence, particularly generative AI powered by large language models (LLMs), could upend many coders’ livelihoods. But some experts argue that AI won’t replace human programmers—not immediately, at least.
“You will have to worry about people who are using AI replacing you,” says Tanishq Mathew Abraham, a recent Ph.D. in biomedical engineering at the University of California, Davis and the CEO of medical AI research center MedARC.
Here are some tips and techniques for coders to survive and thrive in a generative AI world.
Stick to Basics and Best Practices
While the myriad AI-based coding assistants could help with code completion and code generation, the fundamentals of programming remain: the ability to read and reason about your own and others’ code, and understanding how the code you write fits into a larger system.
Find the Tool That Fits Your Needs
Finding the right AI-based tool is essential. Each tool has its own ways to interact with it, and there are different ways to incorporate each tool into your development workflow—whether that’s automating the creation of unit tests, generating test data, or writing documentation.
Clear and Precise Conversations Are Crucial
When using AI coding assistants, be detailed about what you need and view it as an iterative process. Abraham proposes writing a comment that explains the code you want so the assistant can generate relevant suggestions that meet your requirements.
Be Critical and Understand the Risks
Software engineers should be critical of the outputs of large language models, as they tend to hallucinate and produce inaccurate or incorrect code. “It’s easy to get stuck in a debugging rabbit hole when blindly using AI-generated code, and subtle bugs can be difficult to spot,” Vaithilingam says.
Artificial intelligence, particularly generative AI powered by large language models (LLMs), could upend many coders’ livelihoods. But some experts argue that AI won’t replace human programmers—not immediately, at least.
“You will have to worry about people who are using AI replacing you,” says Tanishq Mathew Abraham, a recent Ph.D. in biomedical engineering at the University of California, Davis and the CEO of medical AI research center MedARC.
Here are some tips and techniques for coders to survive and thrive in a generative AI world.
Stick to Basics and Best Practices
While the myriad AI-based coding assistants could help with code completion and code generation, the fundamentals of programming remain: the ability to read and reason about your own and others’ code, and understanding how the code you write fits into a larger system.
Find the Tool That Fits Your Needs
Finding the right AI-based tool is essential. Each tool has its own ways to interact with it, and there are different ways to incorporate each tool into your development workflow—whether that’s automating the creation of unit tests, generating test data, or writing documentation.
Clear and Precise Conversations Are Crucial
When using AI coding assistants, be detailed about what you need and view it as an iterative process. Abraham proposes writing a comment that explains the code you want so the assistant can generate relevant suggestions that meet your requirements.
Be Critical and Understand the Risks
Software engineers should be critical of the outputs of large language models, as they tend to hallucinate and produce inaccurate or incorrect code. “It’s easy to get stuck in a debugging rabbit hole when blindly using AI-generated code, and subtle bugs can be difficult to spot,” Vaithilingam says.
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Here's a short roadmap for learning CSS:
1. Basic CSS: Start with understanding selectors, properties, and values to style HTML elements.
2. Box Model: Learn how the box model works, including margin, padding, border, and content.
3. Layout: Dive into CSS layout techniques like display, positioning, and floats.
4. Flexbox: Master CSS Flexbox for creating flexible one-dimensional layouts.
5. Grid: Learn CSS Grid for creating two-dimensional layouts with precise control.
6. Responsive Design: Understand media queries and how to make your designs responsive to different screen sizes.
7. CSS Preprocessors: Explore tools like Sass or Less to enhance CSS development.
8. CSS Frameworks: Familiarize yourself with popular CSS frameworks like Bootstrap or Foundation.
9. Animations and Transitions: Learn to create CSS animations and transitions for interactive web elements.
10. CSS Variables: Understand CSS custom properties (variables) for more maintainable styles.
11. CSS-in-JS: Explore methods like Styled Components for integrating CSS with JavaScript.
12. CSS Methodologies: Consider using BEM, SMACSS, or other methodologies for scalable and maintainable CSS code.
13. Browser Developer Tools: Become proficient in using browser developer tools for debugging and experimenting with CSS.
14. Performance Optimization: Learn techniques for optimizing CSS for faster page loading.
15. Cross-Browser Compatibility: Ensure your CSS works well on various web browsers by testing and using polyfills when necessary.
16. Version Control: Understand how to manage CSS files using version control systems like Git.
17. Accessibility: Learn about creating accessible CSS and adhering to web accessibility guidelines.
18. CSS3 Features: Explore advanced CSS3 features like gradients, transitions, and transformations.
19. CSS Architecture: Study scalable and maintainable CSS architectures and design patterns.
20. Practice and Projects: Apply your knowledge by working on real projects and experimenting with different CSS techniques.
Remember that CSS is a continuously evolving technology, so staying up to date with the latest CSS features and best practices is crucial for becoming a proficient front-end developer.
1. Basic CSS: Start with understanding selectors, properties, and values to style HTML elements.
2. Box Model: Learn how the box model works, including margin, padding, border, and content.
3. Layout: Dive into CSS layout techniques like display, positioning, and floats.
4. Flexbox: Master CSS Flexbox for creating flexible one-dimensional layouts.
5. Grid: Learn CSS Grid for creating two-dimensional layouts with precise control.
6. Responsive Design: Understand media queries and how to make your designs responsive to different screen sizes.
7. CSS Preprocessors: Explore tools like Sass or Less to enhance CSS development.
8. CSS Frameworks: Familiarize yourself with popular CSS frameworks like Bootstrap or Foundation.
9. Animations and Transitions: Learn to create CSS animations and transitions for interactive web elements.
10. CSS Variables: Understand CSS custom properties (variables) for more maintainable styles.
11. CSS-in-JS: Explore methods like Styled Components for integrating CSS with JavaScript.
12. CSS Methodologies: Consider using BEM, SMACSS, or other methodologies for scalable and maintainable CSS code.
13. Browser Developer Tools: Become proficient in using browser developer tools for debugging and experimenting with CSS.
14. Performance Optimization: Learn techniques for optimizing CSS for faster page loading.
15. Cross-Browser Compatibility: Ensure your CSS works well on various web browsers by testing and using polyfills when necessary.
16. Version Control: Understand how to manage CSS files using version control systems like Git.
17. Accessibility: Learn about creating accessible CSS and adhering to web accessibility guidelines.
18. CSS3 Features: Explore advanced CSS3 features like gradients, transitions, and transformations.
19. CSS Architecture: Study scalable and maintainable CSS architectures and design patterns.
20. Practice and Projects: Apply your knowledge by working on real projects and experimenting with different CSS techniques.
Remember that CSS is a continuously evolving technology, so staying up to date with the latest CSS features and best practices is crucial for becoming a proficient front-end developer.
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Infosys Python - Pandas Interview Q & A.pdf
56.8 KB
👉🏻 DO LIKE IF YOU WANT MORE CONTENT LIKE THIS FOR FREE 🆓
Python Cheat Sheet.pdf
677.7 KB
This cheat sheet includes basic python required for data analysis excluding pandas, numpy & other libraries
Pandas basics to advanced.pdf
854.6 KB
Pandas basics to advanced.pdf
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