Featured Projects

Exploring Airbnb Prices in Geneva

With the increasing popularity of Airbnb as an alternative to traditional lodging options, understanding the pricing dynamics of listings is essential for both hosts aiming to maximize their revenue and travelers seeking value for their money. Geneva, being a global hub for finance and diplomacy, has witnessed a surge in Airbnb listings, making it an ideal ground for studying price variations.

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Visualization of Distributions

Background: Understanding probability distributions is fundamental in the field of statistics and data science. This visualization project serves as a comprehensive guide for students. More will come…

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Sex Differences in Falls Among the Elderly Community-Dwelling Swiss Population: A Population-Based Cross-Sectional Survey

Falls among the elderly population are a major public health concern worldwide, particularly in Switzerland. The risk factors, consequences, and prevention measures for falls are well-documented, but there is a gap in understanding the role of gender-specific differences in falls, especially within the Swiss context.

  • Sex Differences in Falls Among the Elderly Community-Dwelling Swiss Population: A Population-Based Cross-Sectional Survey (andrigerber.github.io)

  • My Master Thesis Project at BFH

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Sport Data Analytics for Swiss Ice Hockey

This repository contains the codebase for analyzing shift data in swiss ice hockey games to gain insights into the intensity of player shifts. Event data from the platform kinexon was used to perform a detailed shift analysis, which can be used from hockey teams to analyze their game in regards to the shift intensities of the respective players and blocks in a game.

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Google Play Store Apps Project

In this project, we analyzed the factors influencing app success on the Google Play Store using a dataset of approximately 10,000 Android applications. We performed data preparation including loading, cleaning, and creating new variables. Exploratory data analysis was conducted to understand the data distribution and relationships between variables. Multiple modeling techniques were applied: a linear regression to understand the impact of features on installs, a generalized additive model (GAM) to capture non-linear relationships, generalized linear models including Poisson and negative binomial to handle count data, and logistic regression to classify apps into high and low installs. Additionally, support vector machines (SVM) and neural networks were utilized to enhance classification performance. Cross-validation and model diagnostics ensured robustness, leading to insights on the key factors such as the number of reviews, app size, and price affecting app success.

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About Me

My name is Andri Gerber, and I'm currently pursuing my Master's in Data Science at Hochschule Luzern (HSLU). This unique journey has not only expanded my academic knowledge but also fueled my passion for uncovering insights from complex datasets and translating them into actionable strategies.

This portfolio is a curated showcase of my ongoing projects during my time at HSLU. Through these projects, you will witness my proficiency in various aspects of data science including data preprocessing, exploratory data analysis, predictive modeling, and machine learning algorithm deployment.

My Journey in Data Science at HSLU

At HSLU, I've been fortunate to be a part of an environment that fosters creativity, innovation, and rigorous academic inquiry. Collaborating with a diverse group of peers, mentors, and industry experts, I've worked on a range of projects that address real-world problems using data-driven solutions.