scikit-learn

scikit-learn is a powerful machine learning library for Python. This Skill Tree offers a comprehensive learning path for mastering scikit-learn. Ideal for data science beginners, it provides a structured roadmap to understand ML algorithms, model selection, and evaluation. Through hands-on, non-video courses and practical exercises in a data science playground, you'll gain real-world experience in implementing machine learning solutions.

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-Learn

Discriminant Analysis Classifiers Explained

Exploring Scikit-Learn Datasets and Estimators

Kernel Ridge Regression

Supervised Learning with Scikit-Learn

Model Selection: Choosing Estimators and Their Parameters

Supervised Learning with Support Vectors

Exploring Scikit-Learn SGD Classifiers

Unsupervised Learning: Seeking Representations of the Data

Implementing Stochastic Gradient Descent

Working with Text Data

Gaussian Process Regression and Classification

Dimensional Reduction with PLS Algorithms

Naive Bayes Example

Decision Tree Classification with Scikit-Learn

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