Since I was a kid, I’ve always loved animals. Whether it was visiting the zoo in a new city while on family vacation, or watching episode after episode of Animal Planet shows, animals - and our connection to them as a fellow species - have continued to fascinate and inspire me into my adult life (as nerdy as that might make me!). Thus, practicing my machine learning classification algorithm skills on a zoo animal classifier seemed like a no brainer.
Sarcasm is defined to be “the use of remarks that clearly mean the opposite of what they say, made in order to hurt someone’s feelings or to criticize something in a humorous way” by The Cambridge Dictionary. Used for a varitey of purposes in the media, sarcasm can portray strong opinions and extreme perspectives of current events to provide comic relief and culturally-relevant dialogue.
For hundreds of years, the Olympic Games have existed as a cornerstone of entertainment, culture, and international collaboration. Inspired by ancient Greek traditions, the International Olympic Committee (IOC) - founded in 1894 - hosted the first modern games in 1896 in Athens, Greece. Since then, the games have evolved to include the paraolympic games for athletes with disabilities, greater gender equality with in increase in female athletes, and alternating years for the summer and winter games. Able to adapt to changes in culture, technology, and economies, the Olympic Games have strengthened their relevance and impact in our modern world, an iconic symbol of the relationships and camaraderie that exist across political borders.
Of all the module projects I’ve complete through the Flatiron School data science program, this one proved to be the most challenging thus far. Whereas in the first two projects, students are provided with a dataset and assigned very specific goals to meet, in the third project, students must find their own dataset in order to answer a question of their choosing. Students can either start with a problem and find a dataset fit to solve it or begin with a dataset and develop questions to answer by exploring the data. However, the project must be of their choosing, and involve some sort of classification modeling, in addition to thoroughly addressing the other components of the data science process covered in the first two modules.
While offering numerous challenges, both those of technical nature and those testing my perseverance, this project offered the opportunity to work through the entire OSEMN data science process independently for the first time. Through the experience I gained a better understanding of: (1) what it means to discover passion behind a particular topic, (2) how to obtain usable data from the vast resources available to our society, (3) the deeper conceptual nature of many different models available to data scientists, and (4) how to contextualize these models appropriately within a real-world scenario. In this blog post, I will touch upon various points throughout this process and explain the knowledge I gained, with regards to data science both as a career field and within the technical nature of the work.
Finding a Data Set
2019 was quite the year, as is evident by the flood of memes, opinions, and reflections throughout my social media channels. Whether it’s the government, our ever-dividing political lines, crises at our borders, in our schools and our homes, the looming demise of our planet, and, ultimately, the constant influx of this negativity from Facebook, Instagram, the news, and every other source of media. That’s not to say nothing positive has emerged from this sense of chaos - whether it’s the viral memes of Nancy Pelosi and baby Yoda lifting our spirts, or Greta Thunberg rallying the world around environmental activism, shards of light stream through the gloom that shrouds much of this year. And whether it’s the call to action that many alarmed citizens feel in light of these changes, or simply the fact that this election cycle is the first in which I am away from home and can form (at least seemingly) independent thoughts of political nature, 2019 is the first year I have felt defined and driven by my political beliefs. No matter on which side of the debate one falls, it’s a confusing time and with the future feeling so uncertain, we are all seeking a path forward.