Machine Learning Free Course at Univ Wisconsin Madison

Dr Sebastian Raschka Machine Learning Course

In this post, you will learn about the free course on machine learning (STAT 451) recently taught at University of Wisconsin-Madison by Dr. Sebastian Raschka. Dr. Sebastian Raschka in currently working as an assistant Professor of Statistics at the University of Wisconsin-Madison while focusing on deep learning and machine learning research.

The course is titled as “Introduction to Machine Learning”. The recording of the course lectures can be found on the page – Introduction to machine learning.

The course covers some of the following topics:

  • What is machine learning?
  • Nearest neighbour methods
  • Computational foundation
    • Python Programming (concepts)
    • Machine learning in Scikit-learn
  • Tree-based methods
    • Decision trees
    • Ensemble methods
  • Model evaluation techniques
    • Concepts of overfitting & underfitting
    • Resampling methods
    • Cross-validation methods
    • Statistical tests & algorithm selection
    • Evaluation metrics

By far, these are one of the best lectures on machine learning, I have come across on the internet. You can find some other useful links such as the following in relation to Dr. Sebastian Raschka 

Ajitesh Kumar
Follow me

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. For latest updates and blogs, follow us on Twitter. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking. Check out my other blog,
Posted in Data Science, Machine Learning, Online Courses. Tagged with , , .

Leave a Reply

Your email address will not be published. Required fields are marked *