Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

LinkedIn Learning

Machine Learning with Scikit-Learn

via LinkedIn Learning

Overview

Learn to use scikit-learn, the popular open-source Python library, to build efficient machine learning models.

Syllabus

Introduction
  • Effective machine learning with scikit-learn
  • What you should know before you start
  • Using the exercise files
1. Input and Loading Data
  • What is machine learning?
  • Why use scikit-learn for machine learning?
2. Supervised Learning
  • What is supervised learning?
  • How to format data for scikit-learn
  • Linear regression using scikit-learn
  • Train test split
  • Logistic regression using scikit-learn
  • Logistic regression for multiclass classification
  • Decision trees using scikit-learn
  • How to visualize decision trees using Matplotlib
  • Bagged trees using scikit-learn
  • Random forests using scikit-learn
  • Which machine learning model should you use?
3. Unsupervised Learning
  • What is unsupervised learning?
  • K-means clustering
  • Principal component analysis (PCA) for data visualization
  • PCA to speed up machine learning algorithms
  • scikit-learn pipelines
Conclusion
  • Get started with scikit-learn

Taught by

Michael Galarnyk and Madecraft

Reviews

4.5 rating at LinkedIn Learning based on 738 ratings

Start your review of Machine Learning with Scikit-Learn

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.