optimizing-deep-learning-models
Optimize deep learning models using Adam, SGD, and learning rate scheduling to improve accuracy and reduce training time. Use when asked to "optimize deep learning model" or "improve model performance". Trigger with phrases like ''optimize'', ''performance'', or ''speed up''. '
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill optimizing-deep-learning-models --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Deep Learning Optimizer Optimize deep learning models by tuning optimizers (Adam, SGD), learning rate schedules, and regularization strategies to improve accuracy and reduce training time. ## Overview This skill empowers Claude to automatically optimize deep learning models, enhancing their performance and efficiency. It intelligently applies various optimization techniques based on the model's
What does the optimizing-deep-learning-models skill do?
Optimize deep learning models using Adam, SGD, and learning rate scheduling to improve accuracy and reduce training time. Use when asked to "optimize deep learning model" or "improve model performance". Trigger with phrases like ''optimize'', ''performance'', or ''speed up''. '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill optimizing-deep-learning-models --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.