Python:Sklearn
Sklearn, alternatively known as Scikit-learn, is a free, open-source machine learning library for Python. It includes a wide range of algorithms for both supervised and unsupervised learning. Supervised learning helps with tasks like classification (predicting categories) and regression (predicting continuous values). Unsupervised learning deals with unlabeled data for tasks like clustering (grouping similar data points). This library is popular for its user-friendly interface and seamless integration with other popular Python libraries like NumPy, SciPy, and Pandas.
Installation
The latest version of Sklearn can be installed using pip:
pip install scikit-learn
Python:Sklearn Concepts
- Biclustering
- Clustering
- Covariance Estimation
- Cross Decomposition
- Decision Trees
- Ensembles
- Feature Selection
- Gaussian Processes
- Isotonic Regression
- Kernel Ridge Regression
- Label Propagation
- Linear Discriminant Analysis
- Linear Models
- Linear Regression Analysis
- Multiclass Classification
- Multilabel Classification
- Multioutput Regression
- Multitask Classification
- Naive Bayes
- Nearest Neighbors
- Probability Calibration
- Quadratic Discriminant Analysis
- Quadratic Regression Analysis
- Self-Training
- Stochastic Gradient Descent
- Support Vector Machines
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