May 27 · 7 min read · This is the second post in my Google Advanced Data Analytics Certificate series. Part 1 covers the initial data inspection (Course 1). This post covers Exploratory Data Analysis (EDA) with Python and
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Dec 29, 2025 · 9 min read · Why Stats Aren't Enough I thought .describe() was enough. It gave me the mean, the max, and the median. But then I learned about Anscombe's Quartet. This is a famous dataset where four different groups of data have the exact same statistical properti...
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Dec 29, 2025 · 5 min read · Hey everyone! 👋 Welcome back to my learning journey 🚀This article is not just another Seaborn tutorial. It is a story of how I learned to see data, not just plot it. When I first started data analysis, charts felt like an extra step — something you...
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Oct 19, 2025 · 17 min read · Introduction: Hi there! In this blog, we’ll explore one of the most popular Python libraries for data visualization — "Seaborn". If you’ve ever looked at raw data and thought, “How do I make this understandable?”, then Seaborn is your friend. What is...
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Oct 8, 2025 · 5 min read · Hello beautiful people 👋I’m Muni — a DevOps engineer who’s been living in the world of pipelines, deployments, and YAML files.But lately, everywhere I look — AI, AI, AI! 😅Everyone’s either training a model, building an agent, or making machines thi...
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Aug 29, 2025 · 4 min read · Data Science may sound like magic, but behind the magic are powerful libraries—pre-built collections of functions, algorithms, and tools that make solving data problems faster and easier. Instead of reinventing the wheel, data scientists rely on thes...
Join discussionAug 21, 2025 · 3 min read · When I started my journey to become an AI Engineer, I knew I had to get comfortable with not just coding, but also understanding data, analyzing it, and communicating results. So, I picked something fun and familiar: Netflix’s global catalogue. It so...
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Jul 31, 2025 · 16 min read · Before diving deeper into machine learning models, it’s critical to understand the assumptions that linear regression rests upon. These assumptions — linearity, independence, constant variance (homoscedasticity), and normality of residuals — form the...
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Jul 17, 2025 · 4 min read · It started as a simple assignment. The task? Create a joint plot using Seaborn. I went hunting for the perfect dataset and stumbled on one about health expenditure and life expectancy for the year 1970 - 2020. Sounds serious, right? But something abo...
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Jul 17, 2025 · 11 min read · Cleaning and Preprocessing Telecom & User Data for AI Ever tried teaching a toddler calculus? That’s what it's like asking an AI to learn from raw, messy data. You won’t be getting predictions, you’ll be getting chaos. So before any AI can predict cu...
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