Predicting the number of likes on Instagram with TensorFlow
1 billion people use Instagram every month, which makes it one of the most popular social networks worldwide. Currently, there is an enormous scope market with the potential to be optimized to increase Instagram posts popularity and engagement. In this project, the main goal is to predict the number...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/339937 |
| Acceso en línea: | https://hdl.handle.net/2117/339937 |
| Access Level: | acceso abierto |
| Palabra clave: | Machine learning Social networks Neural networks (Computer science) Natural language processing (Computer science) tensorflow data science deep learning machine learning convolutional neural networks natural language processing keras data augmentation Aprenentatge automàtic Xarxes socials Xarxes neuronals (Informàtica) processament del llenguatge natura Tractament del llenguatge natural (Informàtica) Àrees temàtiques de la UPC::Informàtica |
| Sumario: | 1 billion people use Instagram every month, which makes it one of the most popular social networks worldwide. Currently, there is an enormous scope market with the potential to be optimized to increase Instagram posts popularity and engagement. In this project, the main goal is to predict the number of likes given a post, building a deep learning model. This model will use convolutional neural networks, natural language processing and other deep learning techniques within the TensorFlow framework. The input data is composed of categorical, numerical data, as well as some image and text data. |
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