Machine Learning Field Guide
From Hidden Patterns to Practical Machine Learning. A comprehensive guide covering datasets, preprocessing, model selection, evaluation, and hyperparameter tuning. Built by practitioners, for practitioners.
Understanding core concepts, terminology, and the ML workflow.
Cleaning, transforming, and preparing data for model training.
Choosing algorithms and training models effectively.
Assessing model performance and avoiding common pitfalls.
Taking models from development to real-world applications.
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