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Andrew Ferlitsch
2021-10-04 12:00:59 -07:00
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@@ -10,10 +10,10 @@ The first stage in MLOps is the collection and preparation for the purpose of de
- Data is stored in GCS buckets and/or BigQuery tables.
- Data sources partitioned by level of data wrangling. Typically these are:
- Curated data – real-world data for training.
- Synthetic data - synthetically generated data for pre-training.
- Unlabeled data - data that needs to be labeled, which optionally can be labeled using Vertex Data Labeling service. Some of this data may come from production.
- Noisy - labeled data that needs cleansing.
- Curated data – real-world data for training.
- Synthetic data - synthetically generated data for pre-training.
- Unlabeled data - data that needs to be labeled, which optionally can be labeled using Vertex Data Labeling service. Some of this data may come from production.
- Noisy - labeled data that needs cleansing.
- Data examples are searchable by feature conditions, labeling and metadata – such as the labeling source.
- Data examples can be tagged for train/eval slicing.
- Statistics are collected and stored on the data distribution.