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run it efficiently on different hardware architectures. For example, Google has built TensorFlow, a framework for deep learning allowing users to run deep learning on multiple hardware architectures
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. using programs like PLINK, bigsnpr, regenie, BOLT-LMM, GCTA, LDSC, LDAK, LDpred1/2, PRS-CS, SBayesR, PRSice. Machine learning approaches, e.g. deep learning, autoencoders, XGboost, or penalized regression
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, SBayesR, PRSice. Experience with machine learning approaches, e.g., deep learning, autoencoders, XGboost, or penalized regression. Position within Mental Disorders and Psychotropic Medication Treatment
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