Applied Machine Learning For Healthcare

One of the best and expanding courses on machine learning and neural networking. Although it has been said in this course that you do not need pre-knowledge in any way, but I think if you have some knowledge of deep learning then it would be better to understand this course.

It is not that all the things are good in it, there are some flaws too, but those flaws are reduced, given its price, yet I would like to tell all the things that I felt should be improved.

I did a project on breast cancer detection with an SVM & KNN. The explanation is very superficial. No insights on hyperparameter tuning. I got an accuracy of .68 with SVM with the same dataset. It would have been good to include different measures when the classifier is not able to classify efficiently.

Prose:

• affordable price
• Five project series e.g Breast, Diabetes, DNA classification, Heart disease detection & prediction project

Cons:

• It is not shown how to save the model
• It would have been good to include different measures in several projects.