lightly-ai / lightly-ai/NvidiaTLTActiveLearning
Advantage over training with all data instead of samples
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- Dominant language
- Python
- Stars
- 26
- Forks
- 2
- PR merge metrics
- No merged PRs in 30d
Description
Hi, I just wanna know what is the difference between training with all the 600 samples and training 100 samples first, 200, 300, ....
What does active learning step does? it really select the best images or what? I didn't get clear for me.
Thanks in advance
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First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
Review the tutorial's active-learning workflow and the explanation of how samples are selected. No file or test is identified in the issue, so first locate the relevant tutorial content and compare its staged-sampling process with training on all 600 samples. Done should clearly document the difference and explain what the active-learning step selects.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100