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skill track

Machine Learning Fundamentals with Python

Discover the machine learning fundamentals and explore how machine learning is changing the world. Join the ML revolution today! If you’re new to the discipline, this is an ideal place to start. You’ll cover the machine learning basics with Python, starting with supervised learning with the scikit-learn library. You’ll also learn how to cluster, transform, visualize, and extra insights from data using unsupervised learning and scipy. As you progress, you’ll explore linear classifiers for machine learning in Python, including logistics regression and support vector machines. You’ll finish the track by covering the fundamentals of neural networks and deep learning models using Keras. By the time you’re finished, you’ll understand the essential machine learning concepts and be able to apply the fundamentals of machine learning with Python.

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Loved by learners at thousands of companies

1
Python
Supervised Learning with scikit-learn

Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!

4 hours

George Boorman Headshot

George Boorman

Curriculum Manager, DataCamp

2
Python
Unsupervised Learning in Python

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

4 hours

Benjamin Wilson Headshot

Benjamin Wilson

Director of Research at lateral.io

3
Python
Linear Classifiers in Python

In this course you will learn the details of linear classifiers like logistic regression and SVM.

4 hours

Mike Gelbart Headshot

Mike Gelbart

Instructor, the University of British Columbia

4
Python
Introduction to Deep Learning in Python

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.

4 hours

Dan Becker Headshot

Dan Becker

Data Scientist and contributor to Keras and TensorFlow libraries

5
Python
Machine Learning Fundamentals in Python
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