Scikit-Learn Tutorial | Machine Learning With Scikit-Learn | Sklearn | Python Tutorial | Simplilearn
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Scikit-learn is a simple and efficient open-source library for data mining and analysis, built on numpy, scipy, and matplotlib. It supports various applications including regression for stock price prediction, classification for customer segmentation, model selection for improving accuracy, clustering for model efficiency, and preprocessing for data transformation. The library is designed to be commercially usable under a BSD license.
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Scikit-Learn Tutorial | Machine Learning With Scikit-Learn | Sklearn | Python Tutorial | Simplilearn
- 1. Types of Plots SCIKIT LEARN TUTORIAL 1
- 2. What is scikit-learn? Simple and efficient tool for data mining and data analysis Built on NumPy, SciPy, and matplotlib Open source, commercially usable - BSD license
- 3. Identifying which category an object belongs to Application: Spam detection What we can achieve using scikit-learn Regression Predicting an attribute associated with an object Application: Stock prices prediction Classification
- 4. Automatic grouping of similar objects into sets Application: Customer segmentation What we can achieve using scikit-learn Model Selection Comparing, validating and choosing parameters and models Application: Improving model accuracy via parameter tuning Clustering
- 5. Reducing the number of random variables to consider Application: To increase model efficiency What we can achieve using scikit-learn Pre- processing Feature extraction and normalization Application: Transforming input data such as text for use with machine learning algorithms Dimensionality reduction