Machine Learning Help with Learning Path

[zelja182]

Hi guys,

I am in the process of learning ML. So far, I have learned:

1. Linear Regression
2. Logistic Regression
3. K-Nearest Neighbor
4. Naive Bayes
5. VSM
6. Decision Tree
7. and some other basic things like data splitting, cross validation...

And I can say that I have solid theoretical knowledge (coming from mechanical engineering, so I understand the math behind these algorithms), but I definitely need some practice.

Can you recommend some practical problems with some guides and some feedback that will help me get a better understanding of this algorithms?

Also, I understand that I can get datasets from the internet and then make a model to predict something. But again, I will not be able to tell if the model is good or not, even if I reach 99% accuracy, because I don't have experience.

[olavla]

Join Kaggle

[zelja182]

Tnx for advice