As a newbie to Python and machine learning, I initially found the course quite challenging. However, after going through the material a few times, the concepts began to click. The course does a great job introducing key machine learning techniques like Decision Trees and Random Forests, and it was particularly helpful in explaining how to interpret feature importance and model behavior. While some prior familiarity with Python would definitely help, the hands-on approach using real-world data made the learning process more engaging. This course served as a solid stepping stone for me into the world of interpretable machine learning. I now feel more confident exploring model evaluation and understanding what drives predictions.

The pdp library did not match the project requirements

The course explains interpretable machine learning concepts in a clear and simple way. The examples and guided project are easy to follow and understand. It helps in understanding how machine learning models make decisions. The content is useful for beginners and practical learning. Overall, it is a good course to improve knowledge in machine learning applications

I was looking for this content for very long time, I will finish all the series. Keep doing great guided projects.

Pretty Informative and crisp to the point. Great hands on course.

Very hands-on. Love it. Thank you!

completed

superb

Good course content

good