A machine learning-based tool to predict playability for games
Material type:
TextPublication details: Islamabad (unpublished) 2021Description: x, 36 p. : ill., Col., ; 30 cm. +CDSubject(s): DDC classification: - 006.312 NOM
| Item type | Current library | Call number | Copy number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|
Thesis
|
Main Campus | 006.312 NOM (Browse shelf(Opens below)) | 1 | NOT for LOAN | 68110 |
Browsing Main Campus shelves Close shelf browser (Hides shelf browser)
|
|
|
No cover image available |
|
|
|
||
| 006.312 LEA Learning spark | 006.312 LES Mining of massive datasets | 006.312 MOL Interpretable machine learning | 006.312 NOM A machine learning-based tool to predict playability for games | 006.312 ROI Data mining | 006.312 RYZ Advanced analytics with spark | 006.312 SAL IBM SPSS modeler essentials |
Submitted in fulfillment of the requirements for the degree of Master of Sciences in Software Engineering to the Faculty of Computing.
Includes bibliographical references
Thesis supervisor: Dr. Adeel Zafar
Thesis (MS)--Riphah International University, 2021
English
There are no comments on this title.