When I first started using scikit-learn, I was overwhelmed with the number of classes and options available. I just chose some basic classifiers I was familiar with and stuck with most of the default settings. The book explains many of the other models and when they would be useful, but also spends a lot of time exploring the datasets (using pandas), preprocessing data and building data pipelines, finding the best hyperparameters, best ways to evaluate a models performance, etc. The library feels less like a big bag of algorithms now and more like a cohesive data pipeline.
http://shop.oreilly.com/product/0636920052289.do
When I first started using scikit-learn, I was overwhelmed with the number of classes and options available. I just chose some basic classifiers I was familiar with and stuck with most of the default settings. The book explains many of the other models and when they would be useful, but also spends a lot of time exploring the datasets (using pandas), preprocessing data and building data pipelines, finding the best hyperparameters, best ways to evaluate a models performance, etc. The library feels less like a big bag of algorithms now and more like a cohesive data pipeline.