COURSE

Machine Learning in Python: Intermediate

Dive more into Machine Learning

In this course, you'll learn Machine Learning with Python, including multi-class classification, linear regression, k-means clustering, gradient descent and neural networks.

By the end of this course, you'll be able to:

  • Understand and apply intermediate linear regression and logistic regression concepts.
  • Understand how to prevent overfitting, a common problem in machine learning.

Course Info:

Machine Learning in Python: Intermediate

Intermediate

The average completion time for this course is 10-hours.

This course requires a premium subscription and includes four missions and one guided project.  It is the 21st course in the Data Scientist in Python path.

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Learn Intermediate Machine Learning Techniques

Logistic Regression

Learn the basics of logistic regression and classification.

Introduction to Evaluating Binary Classifiers

Learn how to evaluate a classification model.

Multiclass Classification

Learn how to use logistic regression with multiple categories.

Overfitting

Learn how to detect overfitting and about the bias-variance tradeoff.

Clustering Basics

Learn how to use clustering to group senators using voting patterns.

K-Means Clustering

Learn to create and interpret scatter plots to explore relationships between variables.

Predicting the Stock Market

Use machine learning techniques to predict the price of the SP500.