- Location
- Saskatoon, Saskatchewan, Canada
- Bio
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University student studying computer science planning to graduate in 2023. Interested in all aspects of software development including deep learning in TensorFlow and web development. Proficient in Python, Java, and C.
- Portals
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Vancouver, British Columbia, Canada -
Saskatoon, Saskatchewan, Canada
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- Categories
- Website development Software development Machine learning Artificial intelligence
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Achievements
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Recent projects
Automatic Home analysis
Positions available: 3-4 students in 1 team or 4 students individually We are a technology company helping realtors find the dream homes for their clients. Our idea is to make searching for properties as customizable as possible. Requirements: - familiar with machine learning concepts - familiar with classification problem solving (nice to have) - familiar with python Further information can be discussed under NDA.
Programming Projects: Python, Liquid/CSS/HTML, VBA, APIs - Level UP
12 Positions Available We're looking for students with solid experience in one or more of the following technology areas to tackle technology projects on our list of priorities: Python Liquid/CSS/HTML Visual Basic (VBA/ Advanced Excel Formulas/Marcos) Graph QL and/or REST API Integrations You bring solid technical experience and enthusiasm to code business solutions. We'll help you build your portfolio of coding accomplishments to talk about in future interviews. We have a pending list of interesting programing projects that we want done and will match candidates to a subset of the following priority projects.
AI/ML Project - Predictive Tool for Embryo Images to Improve IVF Success Rate
In-vitro fertilization (IVF), as the most common fertility treatment, has never reached its maximum potentials. Systematic selection of embryos with the highest implementation potentials is a necessary step toward enhancing the effectiveness of IVF. The embryologist evaluates embryo viability by manual microscopic assessment of its components. With the success of deep learning in the medical diagnosis domain, semantic segmentation has the potential to detect crucial components of human embryos for computerized analysis. Manual assessment of embryos components is a crucial task that involves careful observation by embryologists, and this process can be automated using artificial intelligence (AI)-based algorithms. In this project, students are to work with an existing trained model with algorithm that analyzes embryo images and create a predictive tool to assess the embryo's viability.