Hi, I'm Chris
Buenas at Kumusta, I'm Chris Fornesa and I build experiences and solve problems using code, AI, design, and resource available at my disposal.
Academic Data Projects
The following are a set of select academic projects that I created using the skills that I have learned, thus far, from my current Master's in Data Science program.
Body Fat Dataset Final Project
For the final project for one of my data science courses, I was tasked to utilize my skills to implement a comprehensive data analysis on the Body Fat Dataset. This analysis involved using the Pandas, Numpy, and Matplotlib Python libraries to create selections, pre-process data, and visuals relevant to finding exploratory data analysis insights from the Body Fat Dataset.
Steps that I took for this analysis include:
Choosing the dataset (then loading it).
Describing the dataset.
EDA on the Body Fat Dataset.
Plotting a feature correlation matrix.
Experimenting with 3 unfamiliar regression modelling techniques.
Creating a basic Implementation for the new regression modelling techniques.
5-fold cross-validation for the new regression modelling techniques.
Pipelines for the new regression modelling techniques.
Answering why more complex decision trees may not be better.
Choosing the best model.
Breast Cancer Wisconsin Dataset (BCWD) Final Project
For the final project for one of my data science courses, I was tasked to utilize my skills to implement a comprehensive data analysis on the Breast Cancer Wisconsin Dataset (BCWD). This analysis involved using the Pandas, Numpy, and Matplotlib Python libraries to create selections, pre-process data, and visuals relevant to finding exploratory data analysis insights from the BCWD.
Steps that I took for this analysis include:
Choosing the dataset.
Describing the dataset.
Plotting the histograms.
Comparing the column pairs.
Performing OLS regression to find the average loss over the entire dataset.
Finding the single best feature to predict a diagnosis?
Finding a column pair of input columns with a visible dependency.
Performing principal components analysis (PCA) on all features.
Finding the highest correlative feature pair.
Identifying an outlier of interest.
Personal Data Projects
The following contains a slide deck of dashboards and a set of select personal projects that I have created on my own volition using my data science knowledge.
Fornesus Web Scraping Project
This Jupyter notebook reviews the steps that I took in creating my first web scraping project, using BeautifulSoup4 and Requests Python libraries to scrape data from three of my websites. I also went through the ways in which I integrated GitHub Copilot in this workflow, though I will state that a solid foundation in Python was still necessary for me to refactor this code as efficiently as possible. You can find the associated Colab Notebook at this link.
Links to a live web output of each of the three tests can be found at the following links:
The associated website was created using the Flask template at Replit and Replit's native AI feature. You can find the codebase for this site at this link.
Python Syntax Medical Insurance Project
This is my first Jupyter Notebook which I created using the instructions provided by Codecademy's guidelines and template. You can find the associated Colab Notebook at this link.
Skills Certificates
We have made quality our habit. It’s not something that we just strive for – we live by this principle every day.