Niklaus Geisser's repositories
cypress-tech-talk
Cypress tech talk for Assuresoft
langchain
Tutorial for langchain LLM library
tennis-kata
Implementation of a simple tennis game using react/redux and nodejs
portfolio
My personal website
Twitter-Popularity-Tracking-App
Implementation of a twitter popularity tracking app using RxJs and React
coverage-hole-detection-simulator
Implementation of an algorithm that detects coverage holes in wireless sensor networks applying computational geometry
joke-generator
Jokes Generator using Remix
twitter-clone
Building a Twitter clone using NextJs and Sanity.io
design-patterns
Examples of design patterns in Java
tinder-clone
Building a Tinder clone using React Native and Typescript
Semantic-release-demo
Semantic release demo
spring-petclinic
A sample Spring-based application
spring-petclinic-reactjs
ReactJS (with TypeScript) and Spring Boot version of the Spring Petclinic sample application
effective-oauth2-with-spring-security-and-spring-boot
Demo code for pluralsight course: https://app.pluralsight.com/library/courses/oauth2-spring-security-spring-boot
Pizza-Menu
Application that manages a Pizza Menu using NodeJS, React and Redux.
DocumentTracker
Use Augmented Reality to track documents.
ps-spring-data-jpa
This repository will be a starting point and aid for those taking the Spring Framework: Spring Data JPA course on Pluralsight
clinical-decision-support-systems-exercises
Exercises for the course "clinical-decision-support-systems"
spark-decision-tree-learning
Implementation of a decision tree learning algorithm (ID3) using spark
Optical-Character-Recognition
Optical Character Recognition System, employing Convolutional Neural Network models
data-representation-reduction-exercises
Exercises from laboratories from the course Data Representation Reduction and Analysis
spring-data-overview-pluralsight
Pluralsight course material for Spring Data Overview
Hands-On-Reinforcement-Learning-With-Python
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
feature-selection-example
Feature Selection is the process where features which contribute most to the prediction variable are selected (manually or automatically)
BinarySpacePartitioning
Program that empirically evaluates the expected size (number of cells) of a random binary space partition. This empirical measure will be compared to the upper bound n + 2nHn = O(nlogn)
lex-flex-scanner
Exercises from session 11 from Introduction to language theory and compiling course