Feb 2 · 9 min read · 💡Hey — It's Bittu Sharma👋 We should learn Kubernetes in Docker (KIND) to quickly spin up lightweight, multi-node Kubernetes clusters for local development and CI/CD testing, enabling faster iteration and production-like environments on our machin...
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Feb 2 · 10 min read · 💡 Hey — It's Bittu Sharma 👋 We should learn EKS with Karpenter because it delivers high-performance, cost-optimized, and intelligent autoscaling for modern Kubernetes workloads. Mastering it enables engineers to build production-ready, self-sca...
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Jan 25 · 5 min read · Sometimes slowing down gives you the clarity that rushing never could. 🎯 I learned this lesson the hard way during my MLOps journey. While preparing for interviews, I made the tough decision to pause my MLflow learning - not quitting, just prioritiz...
Join discussionJan 18 · 4 min read · So far: Day 1 → What MLOps is and why it matters Day 2 → The ML lifecycle from idea to production Day 3 → Data engineering basics and data pipelines Today we answer a very important question: Why do ML models get worse over time, even if they were ac...
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Jan 18 · 10 min read · Functions In this lesson, you'll learn how to create and use custom functions in Python. So far, we've worked with built-in functions like print, len, and input, and we've distinguished between functions and methods. In Python, functions can come fro...
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Jan 18 · 3 min read · In this lesson, we explore the importance of variables in Python and how they give context to arithmetic operations. Variables serve as containers for values, enabling us to write more meaningful and maintainable code. Introducing Variables with a Re...
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Jan 18 · 4 min read · When writing programs in Python, operators are essential for performing calculations. This guide explores the seven primary arithmetic operators: exponentiation, multiplication, division (including true division and floor division), modulo, addition,...
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Jan 18 · 4 min read · Now that our Python environment is set up, let's run our very first program and observe its output. When you execute the following line of code: >>> print("Hello future Python programmer!") Hello future Python programmer! Python displays exactly the...
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Jan 17 · 5 min read · You've been building APIs, deploying containers, managing CI/CD pipelines... and now someone mentions "training a model" and suddenly everyone's talking about GPUs, Jupyter notebooks, and something called SageMaker. And you're like, wait. I thought w...
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Jan 15 · 2 min read · Machine learning–based intrusion detection systems often look impressive in notebooks but fall apart when applied to real network traffic.The problem usually isn’t the algorithm, it’s the design assumptions behind the system. I’m currently building a...
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