Ask Madhukar - Techbytes

The keyboard shortcuts to copy, cut, and paste can be boiled down into three characters that utilize Vim-specific terminology. Understanding these terms will help you recall the correct keyboard shortcut. Y stands for “yank” in Vim, which is conceptually similar to copying. D stands for “delete” in Vim, which is conceptually similar to cutting. P stands for “put” in Vim, which is conceptually similar to pasting. I deliberately use the phrase “conceptually similar to” because these actions are not one and the same. If you want to dive deeper into this explanation, scroll down to the section below titled “What Happens Under the Hood?” Copy, Cutting, and Pasting in Vim/Vi - The Basics 1.Press esc to return to normal mode. Any character typed in normal mode will be interpreted as a vim command. 2.Navigate your cursor to the beginning of where you want to copy or cut. 3.To enter visual mode, you have 3 options. We suggest using visual mode because the selected characters are highlighted, an...

- Designing Data-Intensive Applications by Martin Kleppmann Amazon: https://amzn.to/4dlfPed - Database Internals by Alex Petrov Amazon: https://amzn.to/3YI515e - System Design Interview (Volume 1) by Alex Xu Amazon:  https://amzn.to/3WJzwVV   - System Design Interview (Volume 2) by Alex Xu Amazon:  https://amzn.to/3M7zEtv   - Grokking the System Design Interview https://lnkd.in/ebEwFWbP - Grokking the Advanced System Design Interview https://lnkd.in/e_c2CWge - Donne Martin's System Design Primer https://github.com/krmadhukar/system-design-primer - Site Reliability Engineering: How Google Runs Production Systems https://lnkd.in/edYzQwXW - The Site Reliability Workbook: Practical Ways to Implement SRE https://lnkd.in/e9tKypna - Understanding Distributed Systems https://amzn.to/4fGzg2H - Fundamentals of Software Architecture - Mark Richards & Neal Ford https://amzn.to/3Xdozxv - Software Architecture: The Hard Parts - Mark Richards & Neal Ford https:...

  Free AI/ML LLM Fundamentals Course Save 1000s of dollars. Bookmark this and follow the curriculum below. You want to learn AI/ML LLM? I have curated the Best FREE AI/ML roadmap that covers essential knowledge about maths, Python, NNs with hands-on projects Learning. 🙏 Help me spread the free courses! Kindly like, repost and comment! ♻️ Google Courses https://www.cloudskillsboost.google/?qlcampaign=6y-in1-event-90 𝟭. 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝘀 𝗳𝗼𝗿 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 • Linear Algebra - 3Blue1Brown: https://lnkd.in/ejApha3z • Immersive Linear Algebra: https://lnkd.in/ekaUs4Wz • Linear Algebra - KA: https://lnkd.in/emCEHTq5 • Calculas - KA: https://lnkd.in/emCEHTq5 • Statistics and Probability - KA: https://lnkd.in/e6_SirMr 𝟮. 𝗣𝘆𝘁𝗵𝗼𝗻 𝗳𝗼𝗿 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 • Real Python: https://realpython.com • Learn Python - freecodecamp: https://lnkd.in/ejfBftNf • Python Data Science: https://lnkd.in/g4ZysfEe • ML for Everybody: https://lnkd.in/ehR6xaG...

1 Introduction Generative Al imp.i384100.net/5gNjVj 2. Generative AI with Large Language Models imp.i384100.net/k0qRez 2 a) React Fundamentals imp.i384100.net/9gYeRW 2 b) Angular: imp.i384100.net/eKWR9r 2 c) SEO: imp.i384100.net/xkGnW5 3. Generative Adversarial Networks (GANs) Specialization imp.i384100.net/DKNLPn 4. Introduction to Artificial Intelligence (AI) imp.i384100.net/QyQKoA 5. AI Engineering imp.i384100.net/9gYeRy 6. Natural Language Processing Specialization imp.i384100.net/rQPgZR 7. Deep Learning Specialization imp.i384100.net/jrL1k5 8. Generative AI for Data Scientists Specialization imp.i384100.net/k0qReN 9. IBM Data Science Professional Certificate imp.i384100.net/AWNK91 10. Introduction to Data Science imp.i384100.net/GmNDek 11. Learn SQL Basics for Data Science imp.i384100.net/Vm54E3 12. Excel for Business imp.i384100.net/g1EojB 13. Python for Everybody imp.i384100.net/B0MKrL 14. Machine Learning Specialization imp.i384100.net/WqkYnM 15. SQL for Data Science imp.i38410...

If I had to start learning Data Structures and Algorithms from scratch, I would begin with these 20 articles to get a head start: 1) 𝐓𝐢𝐦𝐞 𝐂𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲: https://lnkd.in/gWDD83fm 2) 𝐁𝐢𝐠-𝐎 𝐂𝐡𝐞𝐚𝐭 𝐒𝐡𝐞𝐞𝐭: https://lnkd.in/gsaAWbSs 3) 𝐒𝐨𝐫𝐭𝐢𝐧𝐠 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬: https://lnkd.in/g9npW9JN 4) 𝐋𝐢𝐧𝐤𝐞𝐝 𝐋𝐢𝐬𝐭: https://lnkd.in/gXQux4zj 5) 𝐐𝐮𝐞𝐮𝐞: https://lnkd.in/gJaGSafT 6) 𝐒𝐭𝐚𝐜𝐤𝐬: https://lnkd.in/gBtqxeJH 7) 𝐇𝐚𝐬𝐡 𝐓𝐚𝐛𝐥𝐞𝐬: https://lnkd.in/gCfWr7Eg 8) 𝐇𝐞𝐚𝐩𝐬: https://lnkd.in/gS6SVF5A 9) 𝐑𝐞𝐜𝐮𝐫𝐬𝐢𝐨𝐧: https://lnkd.in/gQiasy8H 10) 𝐁𝐚𝐜𝐤𝐭𝐫𝐚𝐜𝐤𝐢𝐧𝐠: https://lnkd.in/g8Vge2p9 11) 𝐓𝐫𝐞𝐞: https://lnkd.in/gRfmJVDf 12) 𝐁𝐢𝐧𝐚𝐫𝐲 𝐒𝐞𝐚𝐫𝐜𝐡 𝐓𝐫𝐞𝐞: https://lnkd.in/g7QYyVWy 13) 𝐓𝐫𝐢𝐞𝐬: https://lnkd.in/gTp3n4CP 14) 𝐁𝐢𝐧𝐚𝐫𝐲 𝐒𝐞𝐚𝐫𝐜𝐡: https://lnkd.in/gKEm_qUK 15) 𝐆𝐫𝐞𝐞𝐝𝐲 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦: https://lnkd.in/gUMnuQ26 16) 𝐃𝐲𝐧𝐚𝐦𝐢𝐜 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: https://lnkd.in/gtXQsyXT 17) 𝐆𝐫𝐚𝐩𝐡 𝐓𝐡𝐞𝐨𝐫𝐲...

If I had to start learning System Design from scratch, I would begin with these 25 articles to get a head start: 1) Scalability: https://lnkd.in/gx-sPXZm 2) Horizontal vs Vertical Scaling: https://lnkd.in/gAH2e9du 3) Latency vs Throughput: https://lnkd.in/g_amhAtN 4) Load Balancing: https://lnkd.in/gQaa8sXK 5) Caching: https://lnkd.in/gC9piQbJ 6) ACID Transactions: https://lnkd.in/gMe2JqaF 7) SQL vs NoSQL: https://lnkd.in/g3WC_yxn 8) Database Indexes: https://lnkd.in/gCeshYVt 9) Database Sharding: https://lnkd.in/gMqqc6x9 10) Content Delivery Network (CDN): https://lnkd.in/gjJrEJeH 11) Strong vs Eventual Consistency: https://lnkd.in/gJ-uXQXZ 12) Batch Processing vs Stream Processing: https://lnkd.in/g4_MzM4s 13) Concurrency vs Parallelism: https://lnkd.in/gSKUm2Nh 14) Synchronous vs. asynchronous communications: https://lnkd.in/gC3F2nvr 15) Rest vs RPC: https://lnkd.in/gN__zcAB 16) CAP Theorem: https://lnkd.in/g3hmVamx 17) Reverse Proxy: https://lnkd.in/gFwWFDu8 18) Domain Name System...

  One of the golden rule of programming is : 💡 Don’t code today what you can’t debug tomorrow. Below some advices to improve yourself every day : 👉Master Your Tools: Become proficient in the programming languages, frameworks, and tools relevant to your field. 👉Problem-Solving Skills: Develop strong problem-solving skills to efficiently tackle coding challenges. 👉Debugging Proficiency: Sharpen your debugging skills to identify and fix issues quickly. 👉Algorithmic Understanding: Develop a strong understanding of algorithms and data structures for efficient problem-solving. 👉Code Readability: Write clean and readable code; it helps you and others understand and maintain it. 👉Time Management: Prioritize tasks, set deadlines, and manage your time effectively to stay productive. 👉Continuous Learning: Stay updated with industry trends, new technologies, and best practices to enhance your skills. 👉Testing: Embrace testing methodologies to ensure the reliability and correctness of ...