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Walk into any machine learning conference and ask people about the applications of ML in healthcare and most will respond with the canonical example of using computer vision to diagnose diseases from medical scans (followed by a prolonged debate about “should radiologists be worried about their jobs”). But there exists another source of data, beyond imaging studies, that can change the way we approach health: the electronic health record (EHR).
In a recent paper  published by Google researchers and presented at RecSys 2019 (Copenhagen, Denmark) insight was provided in how their video platform Youtube recommends which videos to watch. In this blogpost I will try to summarise my findings after reading this paper.
Since ancient times China has been an agricultural country, with both huge demand for and large-scale production of a wide range of agricultural products. China’s per capita arable land area however is far less than the world average, and the quality of superior arable land is relatively small.
XGBoost is an algorithm that has recently been dominating applied machine learning and Kaggle competitions for structured or tabular data. XGBoost is an implementation of gradient boosted decision trees designed for speed and performance.