Mathematical Foundations of Machine Learning (Udemy.com)

I would rate this course a solid 4.5 stars. The good news is that the instructor explains concepts very clearly, provides helpful examples, and presents the material in a well-structured way. It’s also very beginner-friendly, making it easy to follow even for people who are new to the topic. The only downside is that the instructor mentioned adding a statistics, optimization section, but it seems those part was missed. If that section is added, this course would definitely deserve a full 5-star rating.

Very good! Even though I am a engineer with years of experience, I still learned a lot of useful information that I could use in my day to day at work to solve complex problems in new and more elegant e efficient ways.

The course covers the basics well enough for you to code through the concepts. While the course is still incomplete the concepts it does cover were easy to comprehend. If you are wondering whether it's worth it or not, consider this course if you want to understand the foundational concepts from scratch and code it in Python.

The curriculum is good overall, but the lectures could be better organized. I would have appreciated more visualizations, as some topics were difficult to follow and felt quite dry without visual support. Furthermore, it would be great to see practical, real-life examples to illustrate the usecase of the mathematics taught here.

I'm in module 1, not super interested in the history. Sped through it, always an option :-). A single slide showing the history and the names would be enough for me along with how the use and understanding of linear algebra changed over time.

Amazing class, none of the other classes goes into these basic details which is fundermental to gaining an accurate intuition to deep learning

Overall Ok, but some of the pytorch code not working any more has to be updated in the code. eg: regression(x_min, my_m, my_b).detach().item() line no longer working , I had to be fixed it. Also it would be better if he could have used standard terminology for eg: loss function he is using the term as cost function , this would be confusing initially.

I returned to school to get my Master's degree in Data Science and I needed a review of the topics in calculus, linear algebra and statistics. This course was perfect because it was targeted to machine learning. I tried a couple of other courses that I thought would be good but Jon did a much better job of explaining topics in a clear and understandable way. Very helpful. Thanks Jon!

First the course is absolutely magnificent. John is a great instructor and makes complicated topics clear. My only regret is that the course is not complete yet, and I have had the course for an extended period of time. I would love to see the rest of the course published on this platform.

When I purchased the course, there were some interesting subjects at the end, like statistics and basic ML. As I worked through the content I started to get to the parts I had most interest, and it was removed. Bit of deception, as I wanted to see the end of the film.