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| Study Project: Predicting Company Revenues Based on Supply Chain Analysis (Part I) |
| Semester: |
| WiSe 2017/18 |
| Veranstaltungsnummer: |
| 8.3349 |
| DozentIn: |
| Prof. Dr. Gordon Pipa |
| Ort: |
| 32/372 |
| Zeiten: |
Di. 16:00 - 18:00 (wöchentlich)
Erster Termin:Dienstag, 24.10.2017 16:00 - 18:00, Ort: 32/372 |
| Beschreibung: |
Prerequisites: Experience in computer vision, python, finance/logistics, time series analysis, and web scraping/automation is highly appreciated.
By utilizing computer vision techniques and modeling, the goal of this project is to predict auto sales numbers for a certain car manufacturer. We will use Raspberry Pis to monitor the supply chain via rail and try to extrapolate from the numbers generated. Nonlinear models will aid in our efforts to see if this data can generalize to certain company statistics. This will require the generation of a model that replicates the logistics chain, such as capacity and shipping schedules. We hope our model will tell us the percentage of the auto deliveries that our recording data explains. This has implications in supply chain optimization, corporate management, and investing. |
| Voraussetzungen: |
| The ideal participant in this project has some background in machine learning and computer vision, and a basic knowledge of neural networks. Some experience with TensorFlow or a similar framework would be of additional benefit. |
| ECTS-Kreditpunkte: |
| 6 |
| SWS |
| 3 |
| Sprache |
| Englisch |
| Weitere Informationen aus Stud.IP zu dieser Veranstaltung |
Heimatinstitut: LE Cognitive Science
In Stud.IP angemeldete Teilnehmer: 11
Anzahl der Postings im Stud.IP-Forum: 2
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