Datacamp notes

This repo documents all the notes I've taken going through datacamp courses. I'll also jot down some random project ideas.

Completed courses:

• Parallel computing with Dask
• Supervised Learning with Scikit-learn
• Unsupervised Learning in Python
• Machine Learning with the Experts: School Budgets
• Introduction to PySpark
• Deep Larning in Python
• Introduction to Time Series Analysis in Python

Scikit-learn supervised learning (Classification, Regression) basic workflow

• Preprocessing data: fill/drop/impute missing data
• Standarlized, normalized, scaled features
• Train_test_split the dataset (test_size, random_state)
• Cross-validation (CV)
• Hyperparameter tuning (GridSearch CV, randomized CV)
• model.fit(X_train,y_train)
• model.predict(X_test)
• Evaluate performance (R2, F1, and score etc.)
• Put everything together using Pipeline.