MLOps / Lifecycle
Experiment tracking, pipelines, registries, feature stores
54
listed
6 of 6
categories in use
89%
carrying a data signal
What is in MLOps / Lifecycle
01Training and fine-tuning25
02Pipelines and workflows21
03Experiment tracking8
04Feature stores5
05Model registries2
06Notebooks2
Training and fine-tuningOPEN25
Training and fine-tuning runs: distributed training, LoRA and adapters, the harness around a job. Deciding which run was better is experiment tracking.
Ordered by attributes answered — the column we hold for most of them. Blank where we hold none.
Amazon SageMaker4 ATTRIBUTES ANSWERED
dstack4 ATTRIBUTES ANSWERED
unsloth4 ATTRIBUTES ANSWERED
Determined AI3 ATTRIBUTES ANSWEREDOonetrainer3 ATTRIBUTES ANSWERED
ray3 ATTRIBUTES ANSWERED
Weights & Biases3 ATTRIBUTES ANSWERED
Megatron Core2 ATTRIBUTES ANSWERED
openmldb2 ATTRIBUTES ANSWEREDSHOWING 12 OF 25All 25 Training and fine-tuning →
A CATEGORY OPENS AT 12 LISTINGS · AN EMPTY ONE KEEPS ITS ROW RATHER THAN BEING HIDDEN, BECAUSE THE GAP IS INFORMATION TOO
Everything in MLOps / Lifecycle
SHOWING THE FIRST 40 OF 54 · THE CATEGORY PAGES HOLD THE REST























