These articles are written after I learn something with a deeper study besides the courses. They are more well-structured than these instant notes which are taken during the courses.
I typically focus on simple and more understandable answers. These posts aren’t the official and complete articles for such practical knowledge. You have to search and establish yourself the precise definitions and effective techniques outside these posts. If you see I’m wrong somewhere, please let me know at the comment section, thanks.
- Understanding the confusion matrix and f1-score A good accuracy is really good?
- Capstone project : Setting up a café in Ho Chi Minh City The final report for the course "Applied Data Science Capstone" given by IBM on Coursera.
- For me only
- Fundamental concepts about Machine Learning What if you're asked about ML and you have to describe it for an amateur/a professional person?
- My favorite repositories on Github You must learn by yourself and don't forget to learn from others!
- Accuracy metrics for model evaluation Understanding some types of errors to evaluate models