How Genify used a Transformer-based model to build a recommender system that outperforms industry benchmarks

The rapid ascension of AI, and more recently of deep learning, comported a succession of many breakthroughs in the field of computer science. These have had a profound impact on both the academic and the business world. In particular, modern deep learning techniques applied to the pre-existing concept of recommender systems has given birth to a new, superior class of neural recommender systems, which are … Continue reading How Genify used a Transformer-based model to build a recommender system that outperforms industry benchmarks

Genify’s experience testing Amazon Personalize: learnings and limitations

Challenges of machine learning Machine learning is a complex field that borrows elements from different areas such as computer science, algebra and statistics. Hence, it is not immediate, even for experts in the field, to build strong machine learning models to solve predefined task. Furthermore, those models should also be optimized with a time-consuming and repetitive hyper-parameters search in order to find the best set … Continue reading Genify’s experience testing Amazon Personalize: learnings and limitations

MovieSearch: a smart movie search engine

MovieSearch is a content specific search engine with the aim to retrieve movie information given the contents of a user’s query. The search engine relies on the OkapiBM25 algorithm and takes into consideration the text present in the overview, the title, the names of the cast, and the production companies of each movie. The backend has been developed with the framework Django while the front-end … Continue reading MovieSearch: a smart movie search engine