Vanessa A (vackermann)

vackermann

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Location:Germany

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Vanessa A's repositories

automatic_dependency_characterization

Research project on "Blackbox Learning of Parametric Dependencies for Performance Models from Monitoring Data" (research paper linked): 2-tier machine learning approach with performance prediction accuracy of 92.8% in case study; allows automatic on-the-fly performance modelling to optimize server utilization without any knowledge about the running application.

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vackermann.github.io.disabled

Jekyll project to build a personal website featuring a project portfolio. Uses Agency Theme for Jekyll.

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ml_practicals

Implementation of concepts discussed in Machine Learning course for better understanding and to get more familiar with numpy, scipy, scikit-learn, matplotlib and tensorflow. Includes CNN to classify MNIST data set, experiments on generative vs discriminative models, plotting learning curves to detect overfitting and my own implementations of Linear Regression and the Naive Bayes Classifier.

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mws-restaurant-stage-1

Starter Code for the Udacity's "Mobile Web Specialist Restaurant Reviews App: Stage 1" Project

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mws-restaurant-stage-2

Development server for students completing stage two of the restaurant reviews project for Mobile Web Specialist Nanodegree

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machinelearning-exercises

Based on the project code for the Udacity ud120 machine learning course.

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Mixare4Browser

Modern browser APIs allow to transfer the concept of MixARE http://www.mixare.org (Mixed Augmented Reality Engine) for Web Browser. Mixare4Browser will be able to read the JSON file exported from Mixare4JSON https://github.com/niebert/Mixare4JSON and display the database in the known MixARE way in Firefox, Chromium, ...

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shp2obj

Converts shapefile to obj file, to generate 3D city models based on building footprints and - if available - LiDAR-derived building height data.

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2048-game

Implementation of popular 2048 game in Java. GUI built with Javafx.

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scheduling-algorithms

Implementation of a heurstic algorithm for solving a resource-constrained problem by suggesting and switching assignments.

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