- Scikit Learn Tutorial
- Scikit Learn - Home
- Scikit Learn - Introduction
- Scikit Learn - Modelling Process
- Scikit Learn - Data Representation
- Scikit Learn - Estimator API
- Scikit Learn - Conventions
- Scikit Learn - Linear Modeling
- Scikit Learn - Extended Linear Modeling
- Stochastic Gradient Descent
- Scikit Learn - Support Vector Machines
- Scikit Learn - Anomaly Detection
- Scikit Learn - K-Nearest Neighbors
- Scikit Learn - KNN Learning
- Classification with Naïve Bayes
- Scikit Learn - Decision Trees
- Randomized Decision Trees
- Scikit Learn - Boosting Methods
- Scikit Learn - Clustering Methods
- Clustering Performance Evaluation
- Dimensionality Reduction using PCA
- Scikit Learn Useful Resources
- Scikit Learn - Quick Guide
- Scikit Learn - Useful Resources
- Scikit Learn - Discussion
Discuss Scikit Learn
Scikit-learn (Sklearn) is the most useful and robust library for machine learning in Python. It provides a selection of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction via a consistence interface in Python. This library, which is largely written in Python, is built upon NumPy, SciPy and Matplotlib.
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