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MSc. Artificial Intelligence and Data Science
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Assessing your cultural and operational fit
clustering-of-fault-message-texts
April 29, 2023 – November 20, 2024
Semester Project in collaboration with BMW AG & Technische Hochschule Deggendorf on the topic "Clustering of Fault Message Texts from Machine Equipment"
View ProjectTime-Series-Forcasting
March 10, 2023 – July 25, 2024
Time-Series-Forcasting — GitHub repository
View ProjectObject-Detection
February 8, 2023 – February 8, 2023
Object-Detection — GitHub repository
View ProjectIBM-Stock-prediction
December 3, 2022 – December 3, 2022
The aim of this project is to practice RNN and compare three different models for the stock prediction i.e., Feed-forward neural network(Sliding window), Recurrent neural network(RNN), Long Short Term Memory(LSTM). Data set used was from kaggle.
View Projectproject-Tycho-DV
July 9, 2022 – July 9, 2022
Performing EDA on the data set provided by Project Tycho using R programming
View ProjectFinalYearProject
May 22, 2018 – May 22, 2018
IoT based prediction of stress using machine learning techniques
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong focus on personal projects related to data science and machine learning, indicating self-driven learning and initiative. The collaboration with BMW AG suggests an ability to work in a structured environment. However, without information on work experience or team-based projects, it's difficult to fully assess cultural fit. The diversity of projects (stock prediction, stress prediction, fault message clustering, image classification) suggests a broad interest within the data science domain.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are brief, and there are no completed psychometric or English tests to provide insights into communication style, teamwork, or problem-solving approach.