Modern machine learning can be distilled down to a couple of key techniques that are widely applicable. Recent studies have shown that the vast majority of datasets can be best modeled with just two methods:
1. Ensembles of decision trees (i.e., random forests and gradient boosting machines), mainly for structured data (such as you might find in a database table at most companies), use library of scikit-learn.
2. Multilayered neural networks learned with SGD (i.e., shallow and/or deep learning), mainly for unstructured data (such as audio, images, and natural language), use PyTorch or FastAI.
No comments:
Post a Comment