Project SPARTA PH's SP901: Data Science and Machine Learning Using Python | 2.7.1 Supervised Machine Learning

Did you know that SP901 was released before SP202, introducing me to the world of Python programming? My first experience with this computer language left me feeling like a fish out of water, struggling to communicate with the machine, and the machine with me. (Ganti-ganti lang! Haha) 

The journey into Python was demanding, somewhat painful, and at times, I found myself questioning why I was putting myself through it. But without further ado, let me share with you the snapshots of the weekly assignments for this course.

I made it in jpg form for you to type in your own Jupyter Notebook, by taking the time to type out our code in our Jupyter Notebook, we're not just copying and pasting; we're building a deeper knowledge of Python and the exciting world of supervised machine learning.

2.7.1 Supervised Machine Learning

Guidelines:

Using the the Breast Cancer dataset, perform the following techniques for binary classification:

- Logistics Regression

- RF

- SVM

For Improvement: Utilize graphs and charts to provide a more comprehensive models than relying only on the accuracy of trainings and tests.