Dear future peers,
I'm Alex, a Robotics, Cognition, Intelligence M.Sc. student at TUM. With this repository, I share with you my final class project for a UCLA course I have joined during a term abroad. It is one of my smaller projects, but one that I am really proud of! I am aware that this is likely not your typical TMS application. However, I was free to choose the topic, and I think the project reflects a lot of my personality and interests. Moreover, the project was featured as "best of class" at UCLA and shows how to convincingly tell an entertaining story about data - which comes in handy when applied to projects in the business world!
Of course, I have more to offer to you than Data Science: I have considerable practical experience with prototyping, marketing, and problem-solving. Most notably, together with a small team I developed and built an Air Hockey robot with its own AI that was able to compete with human players. Moreover, I founded and managed my own smart-home start-up as part of the inter-university competition "Start-up your Idea - 5€ Business" during my bachelor's program. I promise, you can count on me for the exploration of problem spaces and understanding of customer needs. Additionaly, my techical background enables me to help out in the technical development as well :)
I will be your competent and creative problem expert, whatever our challenges may be!
~ Alex
If you want to take a closer look at my work and studies, check out my LinkedIn: www.linkedin.com/in/alexander-fichtl-a6068a172
Finally, if you are intrested, here is an article about neural networks and pruning that I wrote together with my peers during a Fulbright scholarship at the Massachusetts Institute of Technology: https://medium.com/@Yichabod/pruning-in-brains-and-machines-62e1046f0438
Contents of this repository:
-
"Data Story Final_Alexander Fichtl.pdf" is the upload of my class projects data story and the main document you should look at.
-
"main.R" the single R script including all my R code for the project.
-
"what_makes_us_happy.ipynb" the jupyter-notebook containing some python code for things I really wanted to do but did not have the experience in R. I always tried it in R-Studio first, if I had to give up adn switch to python, I indicated this in the R script via a comment.
-
"responses.csv" is the csv file containing all the data.
-
"columns.csv" is a csv file containing explanations of every variable of the dataset.