How I Learn Data Science Through Studying Other People's Code | #66DaysOfData

In this video I talk about one of my favorite ways of learning data science: Reviewing other people's code. I also include a short example of me going through this process at the end! I think that code review is one of the most overlooked ways to learn data science. When we are starting out, we don't know the possible feature space for data science solutions. We could spend all day thinking about answers in a jupyter notebook and not get anywhere. When we look at how other people solve data science problems, we start to build intuition. First we copy their process, but eventually we learn the logic behind their decision making. This allows to eventually come up with unique data science solutions on our own. I think it is also worth noting that you should diversify your data science learning. Look at multiple notebooks solving the same problem or using the same data science algorithm. You may find that one example makes far more sense to you than another. My process for code review is this: 1) Go through and mark all of the things that I don't understand & open up a window with the documentation for the package if available 2) Go back through and try to understand the code snippet while looking at the code and the documentation together. 3) Implement the solution in my own project. Kaggle notebooks mentioned in the video: https://www.kaggle.com/pmarcelino/comprehensive-data-exploration-with-python https://www.kaggle.com/startupsci/titanic-data-science-solutions https://www.kaggle.com/kanncaa1/data-sciencetutorial-for-beginners https://www.kaggle.com/dansbecker/how-models-work https://www.kaggle.com/dansbecker/your-first-machine-learning-model #66daysofdata link: https://www.youtube.com/watch?v=uXLnbdHMf8w&ab_channel=KenJee 0:00 Intro 1:30 Why is it important to learn from other's code? 4:04 My approach 5:18 Example #DataScience #KenJee ⭕ Subscribe: https://www.youtube.com/c/kenjee1?sub_confirmation=1 🎙 Listen to My Podcast: https://www.youtube.com/c/Kens