Free Stanford AI Course - Computer Vision (CS231N)

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If you’re fascinated by the technology that enables computers to “see” and understand images, this Stanford CS231n: Convolutional Neural Networks for Visual Recognition YouTube playlist is a must-watch treasure trove of knowledge. This curated series of lecture videos brings to life one of the most influential deep learning courses ever created — the one that helped shape modern computer vision. Whether you’re a student, engineer, or AI enthusiast, you’ll find content that’s both inspiring and deeply informative. 

What sets this playlist apart is the balance of rigorous academic insight and hands-on practical examples. Taught by Stanford professors who helped pioneer the field of deep learning for vision, the lectures take you step-by-step through core concepts like convolutional neural networks (CNNs), image classification, localization, object detection, and much more. You’ll gain both the theory and intuition behind the models that power today’s advanced computer vision systems — from autonomous vehicles to facial recognition and beyond. 

One of the greatest benefits of this YouTube playlist is its flexibility. You can learn at your own pace, revisit complex topics whenever you need, and follow along with real code examples and visual demonstrations. There are no deadlines, no tuition, and no rigid classroom structure — just world-class deep learning instruction available to you anytime, anywhere. It’s like having a Stanford computer vision class on demand. 

In a world increasingly driven by visual data and intelligent systems, mastering CNNs is one of the most valuable skills you can develop. Whether you’re building your first project or preparing for a career in AI, this playlist gives you the conceptual foundation and practical confidence to succeed. Dive in today and explore the frontiers of computer vision with some of the leading minds in the field. 

Link to video

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HTTPS certificate industry phasing out less secure domain validation methods

Why Your EdgeRouter Deserves Proper Name Resolution

If you’ve ever stared at your equipment logs trying to figure out which mystery IP address belongs to which device, you already know the pain. Enabling name resolution turns that mess of numbers into actual, human-readable names. Suddenly, instead of “192.168.1.37 did something suspicious,” you see “printer-that-shouldn’t-be-talking-at-3am.” It’s an instant quality-of-life upgrade that makes troubleshooting faster and a lot less rage-inducing.

I did some homework on the Ubiquiti Edgerouters that i manage and found something cool. That’s where **dnsmasq** really earns its keep. It acts as a lightweight DNS and DHCP helper that automatically ties IP addresses to hostnames. Devices grab an address, dnsmasq remembers the name, and your router logs suddenly make sense. No more keeping a separate spreadsheet titled “IPs I Hope I Remember.” It’s like giving your EdgeRouter a cheat sheet for your own network. It also helps resolve names for devices that are not configured in your DNS server like cameras and printers.

Another big win is troubleshooting speed. When name resolution is enabled, firewall logs, traffic stats, and diagnostic tools become way more readable. Instead of mentally translating IPs back to devices, you can immediately see who’s doing what. That means less time decoding numbers and more time actually fixing the problem—or pretending you fixed it and going for coffee.

Best of all, enabling name resolution with dnsmasq is one of those rare networking tasks that delivers big results for very little effort. A small config change makes your network easier to manage, easier to explain, and easier on your sanity. Your EdgeRouter already knows what’s going on; dnsmasq just helps it talk to you in plain English instead of fluent IP-address-ese.

In the video below, I use Wireshark to learn and confirm if the config change actually works.

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What is 5G Network Slicing

 

From the NETSCOUT blog “What Is Network Slicing” explains how network slicing—a cornerstone capability of 5G networks—creates multiple isolated, logical networks over a single physical infrastructure to meet diverse service demands like ultra-low latency, high bandwidth, and massive device connectivity, unlocking new business opportunities and optimized experiences for enterprises and consumers alike. 

The post breaks down how network slicing works across radio access, core, and data domains, highlights key use cases (from IoT to gaming to autonomous systems), and underscores its benefits in generating revenue, improving service quality, and reducing costs. NETSCOUT also showcases its 5G solutions that provide visibility, automation, and SLA assurance for managing and scaling these slices, encouraging organizations to leverage this transformative technology for competitive advantage.

click on the image above to read the blog

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Screenshot or It Didn’t Happen: Why Install Notes Save Your Sanity

 

There’s nothing quite like finishing a hardware install and thinking, “I’ll remember how I set this up.” Spoiler alert: you won’t. That’s where documenting installation details comes in—especially screenshots. 

In my recent Ubiquiti PowerWave radio deployment, every screen grab became a tiny insurance policy against future confusion. Instead of relying on memory (which fades faster than a 5 GHz signal in a concrete building), I captured exactly what the device looked like when everything was working.

Screenshots are especially valuable with gear like Ubiquiti radios, where settings can be buried three menus deep and labeled just differently enough to make you question your life choices. By documenting things like firmware versions, link status, frequencies, power levels, and alignment screens, you create a visual baseline. When something breaks later—and it will—you have a known-good reference instead of guessing what “normal” used to look like.

Another big win is troubleshooting and support. When you open a ticket or loop in another tech, screenshots instantly bring anyone up to speed. Instead of long explanations like “the link was green-ish but only on Tuesdays,” you can just attach proof. In the case of PowerWave radios, having screenshots from the install makes it much easier to spot what changed: a channel width, a DFS event, or a firmware update that quietly flipped a setting behind your back.

Finally, good documentation is a gift to your future self—and to anyone else who has to touch the system later. Whether that’s six months from now during a storm-induced outage or two years later when someone asks, “How was this originally configured?”, your screenshots tell the story. Taking a few extra minutes during the install can save hours of head-scratching later. In short: document early, screenshot often, and let your past self do your future self a solid.

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Free Stanford AI course - ML from Human Feedback (CS329H)

If you’re ready to build a solid foundation in machine learning, this Machine Learning Fundamentals YouTube playlist is one of the best free resources available online. Carefully curated to guide learners step by step, this collection of videos breaks down complex algorithms and concepts into clear, digestible lessons. Whether you’re just starting out or want to strengthen your understanding before diving into advanced topics, these lectures will equip you with essential tools and intuition for real-world machine learning. 

What makes this playlist especially worthwhile is its structured progression through key topics like supervised learning, classification, regression, clustering, evaluation metrics, and optimization techniques. You’ll find that each video builds on the last, making it easy to follow along even if you’re new to the field. The explanations are framed in a way that balances theory with practical insights — so you’ll not only know what works, but why it works.

Another great advantage of this playlist is its learning flexibility. Because it’s hosted on YouTube, you can watch at your own pace — rewind tricky sections, skip ahead when comfortable, and revisit lessons whenever you need a refresher. This makes it perfect for self-paced learners, busy professionals, and students who want a structured yet flexible way to absorb fundamental machine learning skills without the pressure of exams or fixed schedules. 

In today’s data-driven world, understanding machine learning isn’t just an advantage — it’s becoming a necessity. Whether you’re aiming for a career in data science, software engineering, or research, this playlist gives you a solid foundation to build on. Ready to take your first step into the world of intelligent systems? Start watching this machine learning fundamentals playlist today and unlock the concepts that power modern AI.

https://www.youtube.com/watch?v=ApF2OenMgfc

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