Run training and evaluation on ETHUSDT. It will store the checkpoints under checkpoints with ticker name and time interval if don't specify the checkpoint path with --ckpt.
The goal of the exercises below is to evaluate the candidate knowledge and problem solving expertise regarding the main development focuses for the iFood ML Platform team: MLOps and Feature Store dev
This repository contains the official code of OSTAR in "Mapping Conditional Distributions for Domain Adaptation Under Generalized Target Shift" (ICLR 2022).
SupCL-Seq š Supervised Contrastive Learning for Downstream Optimized Sequence representations (SupCS-Seq) accepted to be published in EMNLP 2021, ext