andreastraut Goto Github PK
Name: AndreasTraut
Type: User
Bio: Graduated Diploma Mathematician and Certified Advanced Data Scientist. Certified PowerBI Data Analyst. In love for data, programming and my son😊🥰
Location: Leipheim, Germany
AndreasTraut's Projects
algorithms-data-structures-and-coding
Improve coding skills and enhance skills in algorithmic thinking and data structures.
arbeitsproben
Einen Überblick über meine Arbeit. Habe in Ulm studiert und war als Risikocontroller sowie Auditor in der Finanzbranche tätig. Ein Jahr in Frankreich gelebt und dort meinen Bachelor in Mathematik gemacht. Bin Diplom Mathematiker und Data Scientist. Habe 5 Jahre in der Schweiz gelebt, unter anderem als Big-4-Consultant. Wieder in meiner Heimat Ulm.
deep-learning
Repository showing my deep-learning experiences in tensorflow 2. Explaining different deployment strategies. Using ConvNets, TensorBoard, Docker Container, Colab Cloud.
deep_learning_explorations
Example on the Local Sensitive Hashing (LSH) algorithm. Relevant for Big Data
experiences-with-microsoftazure
My experiences with Microsoft Azure: I will touch different topics in this document, like “configuration steps”, “billing aspects” and “issue solving”.
generate_random_data
"Generate Data" is an application for creating randomized data according to user defined criteria. This documentation should help beginners, who are not familiar with MySQL and PHP.
machine-learning-with-python
Repository showing my machine-learning experiences with Python, SkLearn and Apache Spark. Providing templates to be used for standard ML problems as well for Big-Data ML problems.
powerbi
This repository contains some PowerBI example reports using PowerQuery, DAX and Tabular Editor. You can open my PowerBI report on the novyPro page without installing anything.
pyspark-google-cloud-platform-example
Small PySpark example, where I connected a Jupyter Notebook to Google Cloud Platform (GCP).
visualization-of-data-with-python
Repository showing different visualization techniques on different kind of datasets. Using python, seaborn, matplotlib. Jupyter-notebooks and Spyder IDE.
visualize-results-in-apps
A fast and impressive solution for visualization of data with Streamlit. Userfriendly, efficient and easy to navigate and deploy.
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