ABSTRACT: Machine learning, statistical modeling, and computer science have grown increasingly popular over the years. The field of data science combines these concepts into a field with the goal of maximizing the accuracy of models using computers and their abilities to make connections and do calculations with unmatched efficiency. As an aspiring data scientist, my report serves as a tutorial for the entire process of a data science study. Through a jupyter notebook, I show, with code and some explanation, the process from start to finish. I begin by showing the process of scraping data and importing it directly, and combining data into one dataframe in Python. Then, I provide a tips for cleaning and tidying the data, so that the data is in the most useful form for analysis. I go through the process of adding my own data to my dataframes, that more accurately represents what I am analyzing, and move on to analysis. I show the process of visualizing the data, deciding on what data is most relevant, and selecting the data for modeling. From there, I show how to fit a variety of models, along with explanation for how these models work. I then show how to test results and I run my own real-life examples of testing the data. I analyze the results and the accuracy of the models and conclude with a statement on their effectiveness. WC=231
READER’S PROFILE: I imagine a reader with advanced data science knowledge, who is put off by my thoroughly-explained approach.
READER’S RESPONSE: While your document does provide analysis, it does so in a very slow and tedious way. The explanations are far too long and boring, and as a result, I could barely finish the document.
ABSTRACT: Machine learning, statistical modeling, and computer science have grown increasingly popular over the years. The field of data science combines these concepts into a field with the goal of maximizing the accuracy of models using computers and their abilities to make connections and do calculations with unmatched efficiency. As an aspiring data scientist, my report serves as a tutorial for the entire process of a data science study. Through a jupyter notebook, I show, with code and some explanation, the process from start to finish. I begin by showing the process of scraping data and importing it directly, and combining data into one dataframe in Python. Then, I provide a tips for cleaning and tidying the data, so that the data is in the most useful form for analysis. I go through the process of adding my own data to my dataframes, that more accurately represents what I am analyzing, and move on to analysis. I show the process of visualizing the data, deciding on what data is most relevant, and selecting the data for modeling. From there, I show how to fit a variety of models, along with explanation for how these models work. I then show how to test results and I run my own real-life examples of testing the data. I analyze the results and the accuracy of the models and conclude with a statement on their effectiveness.
WC=231
READER’S PROFILE: I imagine a reader with advanced data science knowledge, who is put off by my thoroughly-explained approach.
READER’S RESPONSE: While your document does provide analysis, it does so in a very slow and tedious way. The explanations are far too long and boring, and as a result, I could barely finish the document.