YoVDO

Machine Learning with Scikit-Learn

Offered By: LinkedIn Learning

Tags

scikit-learn Courses Machine Learning Courses Supervised Learning Courses Unsupervised Learning Courses Linear Regression Courses Logistic Regression Courses Decision Trees Courses Principal Component Analysis Courses K-Means Clustering Courses

Course Description

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

Related Courses

Predictive Analytics: Gaining Insights from Big Data
Queensland University of Technology via FutureLearn Cluster Analysis
University of Texas Arlington via edX Aprendizaje de máquinas
Universidad Nacional Autónoma de México via Coursera Foundations of Data Science: K-Means Clustering in Python
University of London International Programmes via Coursera Image Compression with K-Means Clustering
Coursera Project Network via Coursera