5 Visuals That Completely Changed How I Think About Data Science!

A straightforward look at the diagrams that taught me more than any degree ever could.

Author

Glenda Carnate
November 27, 2025

Read time: 2.5 minutes

Some data science lessons come quietly from books and lectures. Others feel like a wake-up call, forcing you to rethink how you model, learn, and judge your own skills.

I remember when a simple curve made me question if I really understood machine learning. It wasn’t a professor or a paper, but it was a visual that showed me how much of my confidence rested on unchecked assumptions. Suddenly, I doubted what I thought I knew.

As I kept learning, I found that more visuals had the same effect. They didn’t just teach me new methods... they showed me my blind spots, shortcuts, and biases. Each one took away some ego and gave me more clarity. They made me better, not because they looked nice, but because they were honest.

The 5 Visuals That Rewired My Data Science Thinking:

1. The Bias-Variance Curve:

This is when you see that complexity can be mistaken for intelligence. Simple models don’t win because they’re basic, and they win because they’re honest.

2. Causal DAGs:
They make you realize how much of your understanding was just pattern-matching. DAGs don’t give you answers, but they definitely show where your assumptions fall apart.

3. The Loss Landscape:
This is where the idea of elegance ends. Optimization isn’t smooth learning... it’s trying to survive in a messy space you barely understand.

4. Residual Plots:
Nothing humbles you faster. Residuals don’t care about your accuracy score. They reveal the bias you missed, the features you overlooked, and the confidence you didn’t deserve.

5. Information Flow Diagrams:

They show a truth many avoid: building the model is the easy part. The real challenge is in the decisions, pipelines, definitions, and the politics around it.

💡Key Takeaway: 

These visuals didn’t just improve my technical skills... they changed how I see data science. It’s not about hype or perfect screenshots. It’s about humility, careful checking, limits, systems thinking, and responsibility. These visuals took away the illusion of control and gave me something better: honesty. I’m a better scientist because of that.

👉 LIKE this if any of these visuals have challenged your ego before.

👉 SUBSCRIBE now to get daily deep dives that make you smarter in 3 minutes or less.

👉 Follow Glenda Carnate for honest, in-depth data science insights that get to the point.

👉 COMMENT with the visual that humbled you the most. I’d love to hear your experiences.

👉 SHARE this with a data scientist who still focuses only on accuracy screenshots.

Reply

or to participate.