Niklaus Geisser's repositories

cypress-tech-talk

Cypress tech talk for Assuresoft

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langchain

Tutorial for langchain LLM library

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tennis-kata

Implementation of a simple tennis game using react/redux and nodejs

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portfolio

My personal website

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Twitter-Popularity-Tracking-App

Implementation of a twitter popularity tracking app using RxJs and React

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coverage-hole-detection-simulator

Implementation of an algorithm that detects coverage holes in wireless sensor networks applying computational geometry

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joke-generator

Jokes Generator using Remix

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twitter-clone

Building a Twitter clone using NextJs and Sanity.io

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design-patterns

Examples of design patterns in Java

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tinder-clone

Building a Tinder clone using React Native and Typescript

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Semantic-release-demo

Semantic release demo

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spring-petclinic

A sample Spring-based application

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spring-petclinic-reactjs

ReactJS (with TypeScript) and Spring Boot version of the Spring Petclinic sample application

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effective-oauth2-with-spring-security-and-spring-boot

Demo code for pluralsight course: https://app.pluralsight.com/library/courses/oauth2-spring-security-spring-boot

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Pizza-Menu

Application that manages a Pizza Menu using NodeJS, React and Redux.

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DocumentTracker

Use Augmented Reality to track documents.

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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

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clinical-decision-support-systems-exercises

Exercises for the course "clinical-decision-support-systems"

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spark-decision-tree-learning

Implementation of a decision tree learning algorithm (ID3) using spark

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Optical-Character-Recognition

Optical Character Recognition System, employing Convolutional Neural Network models

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data-representation-reduction-exercises

Exercises from laboratories from the course Data Representation Reduction and Analysis

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spring-data-overview-pluralsight

Pluralsight course material for Spring Data Overview

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Hands-On-Reinforcement-Learning-With-Python

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

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feature-selection-example

Feature Selection is the process where features which contribute most to the prediction variable are selected (manually or automatically)

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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)

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lex-flex-scanner

Exercises from session 11 from Introduction to language theory and compiling course

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