Max Melchior Lang's Projects
This is a selection of my worked assignments from the course advanced R programming I took during my Statistics Bachelor @ LMU Munich.
This is the repository of the AnfΓ€ngerpraktikum (Beginner's internship) of our Bachelor Studies at LMU Munich. The topic includes Bundestagswahl 2021 (German elections).
This is a introduction to Python course by the DSA Munich, which Niklas Walter and I created together.
This repository contains a Wordle solver implemented in R that utilizes Bayesian statistics to efficiently guess the correct word in the popular word puzzle game, Wordle. By leveraging the principles of Bayesian updating, this solver iteratively refines its guesses based on feedback from previous attempts.
End-to-end platform for building voice first multimodal agents
FT's Chart Doctor column including a German translation.
The Quant Copula Playground is a Shiny application designed for everyone interested in exploring the dependencies between stock returns using various copula models. This application is inspired by seminal works in the field of copulas, particularly "An Introduction to Copulas" by Roger B. Nelsen.
A repository for our university project at LMU Munich, showcasing our research on mental health utilizing CTIS data.
Small Data Analysis projects I did over one weekend during my semester. Most of them have blogposts on my website.
This is a DiscordBot I programmed for our Students Discord server. It is able to send useful links like lecture periods via the given commands.
This is a shiny application displaying key indices, stocks, cryptocurrencies and much more. The data is from Yahoo Finance.
Unofficial LMU Munich adaptation of the Gemini LaTeX beamerposter theme, tailored for LMU branding. Includes LMU color schemes, logos, and fonts. Features simple design, minimal setup, and customizable themes for university presentations. Contributions welcome. Note: Unofficial, not LMU endorsed.
Unofficial University of Oxford adaptation of the Gemini LaTeX beamerposter theme, tailored for Oxford branding. Includes Oxford color schemes, logos, and fonts. Features simple design, minimal setup, and customizable themes for university presentations. Contributions welcome. Note: Unofficial, not Uni of Oxford endorsed.
This is the code of one of my assignments, which I passed during my Introduction to statistical software course at LMU Munich.
This repository includes an implementation of the Li and Stephens algorithm, a statistical method used for chromosome painting in genetic ancestry inference.
The Lightning β‘οΈ AI Style Guide Assistant & Code Translator is a specialized adaptation of the Lightning Chatbot, designed to assist in maintaining consistency and accuracy in style guides. Leveraging Groq LPUs, it provides real-time style and grammar recommendations, making it an essential tool for editors and writers.
Lightning is an ultra-fast AI chatbot powered by Groq LPUs (Language Processing Units), offering one of the fastest inference speeds on the market as of April 2024. With its advanced natural language processing capabilities and lightning-fast response times, Lightning provides an unparalleled conversational experience.
This is the source code for my personal blog. I host it over Netlify.
This is a shiny app that let's you create a simple portfolio data analysis report.
A Python package designed to detect prompt injection in text inputs utilizing state-of-the-art machine learning models from Hugging Face. The main focus is on ease of use, enabling developers to integrate security features into their applications with minimal effort.
RAG-nificent is a state-of-the-art framework leveraging Retrieval-Augmented Generation (RAG) to provide instant answers and references from a curated directory of PDFs containing information on any given topic. Supports Llama3.1 and OpenAI Models via the Groq API.
The Shiny Chart Doctor is designed to bring the principles and techniques of effective data visualization, as championed by Alan Smith in his FT Chart Doctor column, to a wider audience.
Group project for Oxford University SB 2.2 Statistical Machine Learning
This is my personal repository of statistics notes and learning materials, collected and organized throughout my journey of understanding the vast world of statistics. π Inside, you'll find a range of topics covered from basic concepts to advanced theories, all structured in LaTeX for easy reading and integration with Overleaf.
This repository contains a detailed report and the associated code for a case study on mortgage approvals in the United States, focusing on a dataset of mortgage applications from a (unknown) 1990 U.S. city.