Day 6 felt like things started to connect.
I kicked off data science in Python, getting comfortable with the ecosystem and exploring how Python is used to work with data. Not sure yet where this path will lead, but I’m letting curiosity guide me.
I also spent time doing DSA practice on CodeChef, keeping the habit alive and reinforcing problem-solving alongside theory.
And the highlight of the day — machine learning.
Today, I finally learned my first complete ML algorithm: Linear Regression, along with how cost functions and gradient descent work together to train a model. Seeing the math, intuition, and code align was incredibly satisfying. It finally feels like I’m not just “reading ML,” but actually understanding how a model learns.
What I worked on today
- 🐍 Started data science with Python
- 🧩 Practiced DSA problems on CodeChef
- 🤖 Learned Linear Regression end-to-end (cost function + gradient descent)
One algorithm down many more to come.
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