Any alternative? I am looking for hybrid recommendation libraries such as lightfm that I can use on Spark (with Scala). Hybrid recommender models can deal better with real-world challenges. Thanks a lot! Oct 8, 2018 - A Python implementation of LightFM, a hybrid recommendation algorithm. It is suited for small to middlesized recommender projects – where you don't require distributed training. LightFM is a Python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback, including efficient implementation of BPR and WARP ranking losses. It's easy to use, fast (via multithreaded model estimation), and produces high quality results. Gradient descent algorithm to iteratively find the weights and improve predictions over time. LightFM assumes that ratings 4 or below are negative and the rest are positive. recommender-system apache-spark. Or best would be for me to build a hybrid recommendation system on spark's mllib from scratch, combining the collaborative step and content filtering one. Finding an ideal restaurant is always a struggle for newcomers and sometimes even for local people, who are looking for places new and exciting to go. - lyst/lightfm This takes into consideration the Content that was selected in the past and its Collaborative based on similar users ratings. We use a lightFM model, a very popular python recommendation library that implements a hybrid model. Which makes this a Hybrid System.
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