@inproceedings{saadna_analysis_2022, address = {Singapore}, series = {Smart {Innovation}, {Systems} and {Technologies}}, title = {An {Analysis} of {ResNet50} {Model} and {RMSprop} {Optimizer} for {Education} {Platform} {Using} an {Intelligent} {Chatbot} {System}}, isbn = {9789811636370}, doi = {10.1007/978-981-16-3637-0_41}, abstract = {A chatbot is a software (or machine) that has the ability to talks with a user: it is a virtual assistant that can answer a number of user questions, and providing the correct responses. In the last few years, the use of chatbots is very popular in various fields, such as health care, marketing, educational, supporting systems, cultural heritage, entertainment, and many others. This paper proposes an intelligent chatbot system that can give a response in the form of natural language or audio to a natural language question or image input in different domains of education and will support multiple languages (English, French, and Arabic). To realize this System, we used different deep learning architectures (CNN, LSTM, Transformers), computer vision, transfer learning to extract image features vector, and natural language processing techniques. In the end, after the implementation of the proposed model, a comparative study was conducted in order to prove the performance of this system using image-response model and question-response model using accuracy and BLEU score metrics.}, language = {en}, booktitle = {Networking, {Intelligent} {Systems} and {Security}}, publisher = {Springer}, author = {Saadna, Youness and Boudhir, Anouar Abdelhakim and Ben Ahmed, Mohamed}, editor = {Ben Ahmed, Mohamed and Teodorescu, Horia-Nicolai L. and Mazri, Tomader and Subashini, Parthasarathy and Boudhir, Anouar Abdelhakim}, year = {2022}, keywords = {Artificial intelligence, Chatbot, Education}, pages = {577--590}, }