Machine Learning for Students
ML doesn't have to be intimidating. Here's the AIKO roadmap.
We start with intuition: what is a model? Why do we split data into train and test?
Then we move to scikit-learn — Linear Regression, Logistic Regression, KNN, Decision Trees, k-Means — using Indian datasets like weather, cricket and student marks.
Finally, we add evaluation skills: accuracy is not enough. Confusion matrices, precision, recall and F1 are essential.
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