I recently completed the “Supervised Machine Learning: Regression and Classification” course, which has prompted me to seek hands-on experience to further enhance my understanding and practical skills in Linear and Logistic Regression algorithms. I would greatly appreciate any recommendations for resources that offer practical implementation exercises related to these topics. Additionally, if there are any specific programming exercises or projects available, I would be eager to try them out to reinforce my learning. Thank you in advance for your suggestions!
Seeking Hands-On Resources for Practical Implementation of Linear and Logistic Regression Algorithms
Try an internet search for “UCI Machine Learning Repository”. They have lots of free datasets that you can experiment with.
Also Kaggle has a lot of interesting tutorials and challenges.
There is a project oriented course. Machine learning zoomcamp, it has youtube and github from which you can folllow along. Also jeremy howard is a good option as well