[Free] Practical Machine Learning With Scikit-Learn
Learn the most powerful machine learning algorithms in under an hour – Free Course
What you’ll learn
- How to implement regression, classification and boosting algorithms
- Which algorithms work best for a given dataset
- Data preprocessing
Requirements
- Basic python knowledge
- Google Colab account
Description
Machine learning is a rapidly growing field. However, a lot of courses on the internet today do not go over some of it’s most powerful algorithms. In this course, we will learn multiple machine learning algorithms, along with data preprocessing, all in under an hour. We will go over regression, classification, component analysis and boosting all in scikit-learn, one of the most popular machine learning libraries for python.
Algorithms we’ll go over (in order):
Linear Regression
Polynomial Regression
Multiple Linear Regression
Logistic Regression
Support Vector Machines
Decision Trees
Random Forest
Principle Component Analysis
Gradient Boosting
XGBoost
Author(s): Adam Eubanks
