Marwan Mostafa

M.Sc.
Research Assistant

Contact

Marwan Mostafa, M.Sc.
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Office Hours
nach Vereinbarung/ by appointment
Harburger Schloßstraße 36,
21079 Hamburg
Building HS36, Room C3 0.013
Phone: +49 40 42878 4097
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Research Project

iNeP
Integrated network planning for the electricity, gas and heat sectors

iNeP

Integrated network planning for the electricity, gas and heat sectors

Federal Ministry for Economic Affairs and Climate Action (BMWK); Duration: 2021 to 2026

Publications

TUHH Open Research (TORE)

2023

2022

2021

Courses

Stud.IP
zur Veranstaltung in Stud.IP Studip_icon
Machine Learning I
Semester:
SoSe 23
Veranstaltungsart:
Lecture + Tutorial
Veranstaltungstyp:
Vorlesung (Lehre)
Veranstaltungsnummer:
lv2432_s23
DozentIn:
Nihat Ay, Dr. Manfred Eppe
Beschreibung:
- History of Neuroscience and Machine Learning (especially Deep Learning) - McCulloch-Pitts neurons and binary neural networks - Boolean functions and threshold functions - Universality of McCulloch-Pitts neural networks - Learning and the Perceptron Convergence Theorem - Support vector machines - Harmonic Analysis of Boolean Functions - Continuous artificial neural networks  - Kolmogorov's superposition theorem - Universal approximation with continuous neural networks - Approximation errors and the gradient descent method: the general idea - The stochastic gradient descent method (Robbins-Monro and Kiefer-Wolfowitz cases) - Multilayer Networks and the Backpropagation Algorithm - Statistical Learning Theory
Voraussetzungen:
linear algebra, analysis, basics of programming
Lernorganisation:
lecture + tutorials
Leistungsnachweis:
m1595 - Machine Learning p1543 - Machine Learning: written exam m1595-2022 - Machine Learning I p1543-2022 - Machine Learning I: written exam vl424-2022 - Bonus Tasks
Sonstiges:
Literature:
- An Introduction to Statistical Learning, James, Witten, Hastie, Tibshirani
- Pattern Recognition and Machine Learning, Bishop
ECTS-Kreditpunkte:
6
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Institut für Data Science Foundations (E-21)
In Stud.IP angemeldete Teilnehmer: 168
Anzahl der Postings im Stud.IP-Forum: 20
Anzahl der Dokumente im Stud.IP-Downloadbereich: 37

Supervised Theses

ongoing
completed

2022

  • Barthelme, J. (2022). Technisch-ökonomische Systemmodellierung und -anlayse eines urbanen Quatiers hinsichtlich des Einsatz von Wasserstoff als primärer Energieträger.