100-Days-Of-ML-Code

Why we included this project

100-Days-Of-ML-Code breaks machine learning down into a day-by-day study plan. Each entry pairs a short explanation with working Python code built on scikit-learn, and the datasets you need are included, so you can type along instead of just reading. The path starts with data preprocessing and simple linear regression, then moves through multiple and logistic regression, SVMs, K-NN, naive Bayes, and decision trees. Many days come with an infographic that lays out the math behind the algorithm, which helps build intuition before you open the editor. It is a practical starting point for someone new to ML who wants a structured, hands-on route through the classic algorithms, and it holds up as a reference to come back to later.