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Item Open Access A PROFESSION RECOMMENDER SYSTEM BASED ON DEEP LEARNING AND MACHINE LEARNING APPROACHES(СДУ хабаршысы - 2023, 2023) Iskalinov F.Abstract. The issue of uncertain career path choice among modern schoolchildren has become increasingly prominent, resulting in a substantial decrease in the number of university students. This uncertainty has become a major concern as students and their parents are often unfamiliar with the wide range of available professions, particularly those that have emerged in the last decade. A modern solution is proposed in the form of a web application that uses Deep Learning, Machine Learning, and NLP to recommend suitable specialties based on the competencies required for the profession. The system will analyze and extract implicit features through a supervised classification approach, providing a comprehensive solution for profession search in the Kazakhstan market.Item Open Access DEVELOPMENT OF IMAGE CAPTIONING MODEL BY USING DEEP LEARNING TOOLS(СДУ хабаршысы - 2019, 2019) Kynabay B. ; Aldabergen A. ; Shamiluulu S.Abstract. Automatic formation of image description is one of the most challenging and popular topics in the field of deep learning (DL) for nowadays. In this work image captioning convolutional neural network model (VGG16) is developed by implementing deep learning tools and techniques. Specifically, this work’s resulting product can be implemented in a system that answers to the question, based on the image given. Image captioning includes two main sub-processes: image processing and natural language processing. The model was constructed from 16 layers and it uses Flicker 8K data-set of images for captioning. The model was evaluated by using BLEU metric and its value was nearly 0.75, it takes one image as an input and returns one description for that image.