I haven’t watched the Pinterest videos yet, but I found these, on O’Reilly’s (paid) website:
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How Pinterest uses machine learning to achieve ~200M monthly active users - Yunsong Guo (Pinterest) (28:40 mins)
Pinterest has always prioritized user experiences. Yunsong Guo explores how Pinterest uses machine learning—particularly linear, GBDT, and deep NN models—in its most important product, the home feed, to improve user engagement. Along the way, Yunsong shares how Pinterest drastically increased its international user engagement along with lessons on finding the most impactful features. -
Escaping the forest, falling into the net: The winding path of Pinterest’s migration from GBDT to neural nets - Xiaofang Chen (Pinterest), Derek Cheng (Pinterest) (40:16 mins)
Pinterest’s power is grounded in its personalization systems. Over the years, these recommender systems have evolved through different types of models. Xiaofang Chen and Derek Cheng explore Pinterest’s recent transition from a GBDT system to one based in neural networks powered by TensorFlow, covering the challenges and solutions to providing recommendations to over 160M monthly active users.
They are many more videos on the Safari’s website. But I was allowed to post only two links.