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TechBytes on Linux

This is a growing list of Linux commands which might come handy for the newbies of Linux. 1. Found out i had to set the date like this:    # date -s 2007.04.08-22:46+0000 2. Mounting     sudo mount -t cifs // < pingable_host_or_ip > / < win_share_name > /build -o user= ,domain= ,uid=string,gid=string 3. To install linux packages from internet (ubuntu only)     apt-get install 4. To determine what ports the machine is currently listening on     netstat -an | grep -i listen | less 5. Find in files in Linux     find . | xargs grep 'string' -sl 6. To become superuser/root     sudo -i 7. To find a running process using name ps -aef | grep "searchstring" 8. Alt + F2 opens run window in RHEL 9. To access windows share from linux smb:// /d$ 10. To know the last reboot date & time $ last reboot | head -1 11. To install RPM packages in RHEL rpm -ivh 12. To un-install RPM package in RHEL rpm -e 13. To display Linux Kerne
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Interview preparation Guide for Software Engineers

- 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://amzn.to/4cp3N

Free AI/ML LLM Fundamentals Course

  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! ♻️ 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/ehR6xaGZ • Intro to ML - udacity: https://lnkd.in/eVudd2Zm 𝟯. 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿

Cloud Computing and data storage terminology glossary

1. Control Plane  The control plane provides management and orchestration across an organization's cloud environment. This is where configuration baselines are set, user and role access are provisioned, and applications sit so they can execute with related services. 2. Cloud computing service Types IaaS, PaaS & SaaS Within the cloud deployment models, there are several types of cloud services, including infrastructure, platforms, and software applications. Cloud service models are not mutually exclusive, and you can choose to use more than one in combination or even all of them at once. Here are the three main cloud service models: Infrastructure as a Service (IaaS) IaaS delivers on-demand infrastructure resources, such as compute, storage, networking, and virtualization. With IaaS, the service provider owns and operates the infrastructure, but customers will need to purchase and manage software, such as operating systems, middleware, data, and applications. Platform as a Serv

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Learning Data Structures and Algorithms from scratch

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