My name is Paula Maldonado and I am a French-Chilean with a passion for gaining insights from data. I have an economics background, and after two years of a PhD on theoretical economics, I decided to make a transition to data.
Having taken courses in mathematics, statistics and econometrics, I have focused my learning on doing projects to get more experience and to learn and improve my knowledge of Python, SQL, Power BI and Tableau, as well as HTML and CSS.
This is my portfolio, where most of my projects are published. Go take a look at it !
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Buying and selling a car can be an important financial decision, and thus being able to estimate the selling price of a car is very important.
The objective of this project is to create a web application that allows for user input to estimate the selling price of a car given a number of features using a machine learning estimator and real data collected from the web.
After the release of a new game, it is important to know whether it has been accepted by the community and to know if there are some issues that should be adressed.
The objective of this project is to analyze the tweets to estimate the sentiment and evaluate the success of the game.
IMDb (Internet Movie Database) is one of the biggest online databases regarding films, series, video games and others.
The objective of this project is to explore the available datasets to gain insights about IMDb
Preventing customer churn is a very important matter for a company, as understanding why customers are leaving allows to make better decisions. Moreover, acquiring new customers can be more expensive than keeping old ones.
The objective of this project is to understand why customers may want to leave the company and to train a ML model able to predict what customers are likely to churn.
It is important for a business to forecast sales to better anticipate and make better business decisions, but even more important it is to understand what impact sales and which stores are performing better or worse.
The objective of this project is to gain insights from the data and forecast sales.
This project takes a look at how to use modern technologies to deal with image classification. More precisely, we saw how to build a model using CNNs and transfer learning and we were able to build a multi-class model that achieved 85% accuracy on test data.
Photo by Niels Kehl on Unsplash
During disasters, communication is vital, but it is at such times that disaster response organizations are least able to filter and extract the most important messages.
The objective of this project is to classify messages into several categories to indicate to which organizations they should be referred.
In this guide, we explore HoloViz tools, and most precisely, we take a look at Panel and hvPlot which are open-source libraries that can be used to create interactive charts and dashboards. We also see how easy is to deploy and share our dashboard using a Jupyter Notebook.
Medium Article |
GitHub Repository |
Deployed Dashboard (HerokuApp)
Starbucks’ customers have been randomly selected to receive an advertising promotion to purchase a specific product.
The goal is to analyze the data results to optimize the promotion strategy in order to send the promotion only to those customers who are most receptive to it, to limit the cost of sending the promotion.
Photo by Niels Kehl on Unsplash
A quick look at different global and local methods for explaining complex machine learning models using Python libraries.
In this guide, we take a look at different common tools and concepts used to summarize data to try to better understand how they work and when to use them.
Photo by Cathryn Lavery on Unsplash
The objective of this project, inspired by the book “Hands-On Machine Learning” by Aurélien Géron, is to study linear regression (Normal Equation & Gradient Descent) more so than building an optimal algorithm for regression.