Pranav’s DIYA Experience

DIYA was an extremely rewarding, hands-on summer experience that really dove into what real-world machine learning was like. While it was introductory, it did go into many facets of real-life machine learning. Before joining DIYA, I had very minimal exposure to programming in general, as I had only taken a brief game design course in school. Through the first few weeks, we gained knowledge about how to use the basics of Python through the Kaggle courses as well as how to use some other facets of Python such as NumPy as well as Pandas in order to go through data. We started with basic parts of Python like strings, floats, and booleans and worked my way to defining functions and importing packages. Other than learning about the different parts of Python, we learned about data science and machine learning as a whole through the Coursera courses. Because I didn’t know how to code, it was perfect because it explained it on a theoretical level which did not need the experience of a programmer to understand. From there, we learned how to graph and then started to learn how to use scikit-learn’s models. We learned how to tweak hyperparameters in order to get the best result while keeping them safe enough so my model didn’t overfit or underfit. The problem of a skewed dataset was slightly frustrating, but it did show a side of machine learning that was real that a meticulously curated project that was made for a class and not to actually learn could never have done. Altogether, it was a very educational but also fun experience. There were many things that helped elevate the program from a regular summer program to something that was phenomenal. First, there were the great mentors and TA who through weekly meetings and office hours were able to help our projects run smoothly as well as guide. Another thing that helped enhance the project was the collaboration that all the interns had whether it was finding ways to combat problems like concatenating DataFrames or working on the presentation together. In summary, DIYA was a great project because it was hands-on and collaborative with eager people to work with. It strengthened my love of learning and made me excited about data science in the future.