10 days of Python

Summary

🔥 Day 1–3: Python Power-Up

Started with Python essentials—functions, lambda expressions, decorators, magic methods, and exception handling. Understanding how Python handles data structures and memory was a game-changer!

📊 Day 4–6: Data Wrangling & Preprocessing

From Pandas DataFrames to NumPy arrays, I explored indexing, slicing, aggregations, feature scaling, and handling missing values. Clean data is king in data science!

🏆 Day 7–10: Machine Learning & Feature Engineering

Deep-dived into regression, classification, clustering, PCA, feature engineering, and gradient descent. Seeing how algorithms like Random Forest, SVM, and K-Means optimize predictions was eye-opening!