Jupyter Notebook

Until last year, I heard many wild stories about hackathons, but I had never been to one. Finally, in my first semester at college I got my chance. I worked in a team with other students and we divided responsibilities accordingly. My job was to take a list of users and calculate their relative positions using the Google Distance Matrix API. That night was also the first time I used Python. Things could have gone A LOT better. My code was messy and finding bugs was a nightmare.

Later that same semester, I joined a Python programming club. The older students were raving about this thing called Jupyter Notebook. I decided to switch to Jupyter and I have never looked back. It's just so... convenient. I can organize my code into neat little cells and run the different parts as I see fit. I can try out different versions of functions without worry. We all know that hassle of modifying code. One minute it works fine, the next it has a million errors because you changed who knows what! Now, I don't have to worry about that.

I used Anaconda to download Jupyter Notebook. Anaconda is a data science environment that keeps all of my downloadable libraries organized. They have a tool called the Anaconda Navigator that helps me manage what's installed in each of my custom environments. I highly recommend using Anaconda for this reason. It has come in handy time and time again, especially with my latest endeavor involving AI. At some point I will go over my most recent project: neural networks.

My favorite feature of Jupyter Notebook is the way data is displayed. Whenever I run my code from a cell, a dropdown from the cell shows my formatted output. Looking through my code later, I know what code corresponds to what output. Someone came up with the neat idea of converting this awesome organization style into a presentation. It's called nbpresent. I can take my notebook and show it to my peers through the use of themed slides. The result is effective communication, an indispensable asset.