scikit-learn

scikit-learn is a Python library for machine learning. It provides a wide range of algorithms and tools for data mining and analysis. In this skill tree, you'll learn how to use scikit-learn to build machine learning models in Python.

38 Skills|3 Courses|3 Projects

Quick Start with scikit-learn

Beginner

scikit-learnMachine Learning

In this course, We will learn how to use scikit-learn to build predictive models from data. We will explore the basic concepts of machine learning and see how to use scikit-learn to solve supervised and unsupervised learning problems. We will also learn how to evaluate models, tune parameters, and avoid common pitfalls. We will work through examples of machine learning problems using real-world datasets.

15 Labs

Linear Models in Scikit-LearnStart

Discriminant Analysis Classifiers ExplainedStart

Exploring Scikit-Learn Datasets and EstimatorsStart

Kernel Ridge RegressionStart

Supervised Learning with Scikit-LearnStart

Model Selection: Choosing Estimators and Their ParametersStart

Supervised Learning With Support VectorsStart

Exploring Scikit-Learn SGD ClassifiersStart

Unsupervised Learning: Seeking Representations of the DataStart

Implementing Stochastic Gradient DescentStart

Working With Text DataStart

Gaussian Process Regression and ClassificationStart

Dimensional Reduction with PLS AlgorithmsStart

Naive Bayes ExampleStart

Decision Tree Classification with Scikit-LearnStart

Sklearn Practice Labs

Beginner

Sklearn

This course contains lots of labs for Sklearn, each lab is a small Sklearn project with detailed guidance and solutions. You can practice your Sklearn skills by completing these labs, improve your coding skills, and learn how to write clean and efficient code.

Lab

Sklearn Practice Challenges

Beginner

Sklearn

This course contains lots of challenges for Sklearn, each challenge is a small Sklearn project with detailed instructions and solutions. You can practice your Sklearn skills by solving these challenges, improve your problem-solving skills, and learn how to write clean and efficient code.

Lab