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| PDF Title : | Python for Data Analysis |
|---|---|
| Book Edition : | 2nd Edition |
| Total Page : | 544 Pages |
| Author: | Wes McKinney |
| PDF Size : | 10.1 MB |
| Language : | English |
| Source : | wesmckinney.com |
| PDF Link : | Available |
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Python for Data Analysis: 2nd Edition
scikit-learn is one of the most widely used and trusted general-purpose Python machine learning toolkits. It contains a broad selection of standard supervised and unsupervised machine learning methods with tools for model selection and evaluation, data transformation, data loading, and model persistence.
These models can be used for classification, clustering, prediction, and other common tasks. There are excellent online and printed resources for learning about machine learning and how to apply libraries like scikit-learn and TensorFlow to solve real-world problems. In this section, I will give a brief flavor of the scikit-learn API style.