krishna devli @Coderhackedkd

AI engineering isn’t magic—it’s math + logic + code wrapped in creativity. Once you realize this, you stop chasing hype & start building real impact. ⚡ #AI #MachineLearning #AIEngineer

MCP Servers aren’t just modular—they can self-heal. When nodes fail, they redistribute workloads without downtime. Hidden backbone of critical systems. 💡 #MCP #Servers #Cloud

📌 Learning this gave me a new respect for system architects and engineers who build things that never stop.

🧩 The Big Question for GenZ Coders: 👉 Are we coding because we want to create, or are we coding because the internet has set the vibe and told us this is how we should? This monopoly is subtle — but real. Let’s talk about it.

🧩 The Big Question for GenZ Coders: 👉 Are we coding because we want to create, or are we coding because the internet has set the vibe and told us this is how we should? This monopoly is subtle — but real. Let’s talk about it.

🚀 Want to be an AI Engineer? AI isn’t magic – it’s Math + Logic + Code. 💡 Here’s a roadmap to guide you: Languages, Math, ML & DL. From chatbots 🤖 to self-driving cars 🚘—master this path & build the future! 🌍✨ #AI #MachineLearning #DeepLearning #AIEngineer #Python

💡 Your mission: I optimized “Find common element in two arrays” from O(N²) to O(N) using sets. Think you can do better? Show me your smartest Python trick ⬇️ #Python #CodeEfficiency #DSA #100DaysOfCode

🔥 Challenge for you: I solved this: “Given two arrays, find a common element in O(N) instead of O(N²).” Now it’s your turn! Can you beat my Python set-solution? 💪 Drop your approach ⬇️ Let’s grow together on this #DSA journey!

⚡ Some code crawls, some flies. Why? Algorithms! O(N²) vs O(N log N) can be life-changing. 🎯 Learned Big-O, Big-Theta, Space Complexity & Python tricks for speed + clarity. 💡 Try this: Common element in 2 arrays in O(N). I solved it with sets. Beat me? ⬇️ #100DaysOfCode #Py

📚 Today, I cracked the code on: ✅ Time Complexity – Big-O, Big-Theta, Big-Omega ✅ Space Complexity – How memory silently affects performance ✅ Why Pythonic solutions aren’t just pretty but FAST too. #Python #CodeEfficiency #DSA #100DaysOfCode

⚡ Stop scrolling! Want to know why some code flies while others crawl? It’s all about the Big-O game – choose the wrong algorithm, and you’re stuck in O(N²) chaos 😵… pick the right one, and BOOM ⚡… problem solved in seconds!

When you’re solving a problem in Python, which approach do you trust more?

⚡ Today was all about strengthening my Python foundations: 🔹 Mastered OOPs concepts (Classes, Objects, Inheritance, Polymorphism). 🔹 Practiced Functions & Recursion to deepen logical thinking. 🔹 Revised all Python basics for a strong base.

Did you know? Many think recursion is just repeating a function, but it’s rooted in math and self-referential logic. It can solve tough problems like Tower of Hanoi, maze-solving, or parsing trees in just a few elegant lines.

Check out my latest article: Small Language Models (SLMs): Why Bigger Isn't Always Better. linkedin.com/pulse/small-la… via @LinkedIn

🚀 Today’s Progress: Focused on Discrete Math, Probability, Calculus & Linear Algebra — key skills for any aspiring AI Engineer. Believing in consistent self-learning to build an AI career without college. From today, committing to mastering Data Science, ML, Deep Learning & LLMs

Probability Theory, Calculus, and Linear Algebra are the backbone of AI. Every prediction, optimization, and neural network training depends on them — without these, ML wouldn’t exist 🚀 Today I focused on Discrete Math, Probability, Calculus, and Linear Algebra ...