# Umaraslam66 > Open-source publisher. Listings imported from github.com/Umaraslam66 — credited to the original author with their license. - **Listings:** 13 - **Total installs:** 0 - **Profile:** https://agentstack.voostack.com/s/umaraslam66 - **Website:** https://github.com/Umaraslam66 ## Published listings - [Overfitting First](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-overfitting-first) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-overfitting-first` Use when choosing a model architecture or size, when tempted to add dropout or augmentation or weight decay, when training and validation loss are both bad, or when unsure whether a model is underfitting or overfitting - [Building The Training Skeleton](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-building-the-training-skeleton) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-building-the-training-skeleton` Use when about to report any accuracy loss or metric to anyone, when running or writing a training or evaluation script, when asked for a number from a script you did not write, before launching a real training run, or when a model trains without error but results are unexplained - [Debugging Silent Training Failures](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-debugging-silent-training-failures) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-debugging-silent-training-failures` Use when a model trains without errors but produces bad or implausible results, when loss is NaN or flat or oscillating, when accuracy is suspiciously high, when validation and training curves look wrong, or when eval numbers do not reproduce - [Weakest Hypothesis](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-weakest-hypothesis) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-weakest-hypothesis` Use when inducing a rule, root cause, or lesson from few examples — reflection steps in self-improvement loops, encoding learnings into memory or prompts, diagnosing from a handful of failure reports, or whenever several explanations fit the evidence and one must be adopted - [Designing Ml Experiments](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-designing-ml-experiments) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-designing-ml-experiments` Use when comparing model variants or configs, when a change appears to help but you are unsure the difference is real, when setting up a sweep, or when deciding whether to adopt a change - [Tuning Hyperparameters](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-tuning-hyperparameters) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-tuning-hyperparameters` Use when searching over learning rates or other hyperparameters, when setting up a sweep, when deciding between grid search and random search, or when extracting the last few points of performance before shipping a model - [Shipping Ml Systems](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-shipping-ml-systems) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-shipping-ml-systems` Use when putting a model into production, when deciding whether a problem needs ML at all, when offline metrics look good but production results do not match, or when building serving and training pipelines - [Training Neural Networks](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-training-neural-networks) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-training-neural-networks` Use when training, fine-tuning, or evaluating any neural network or ML model, before writing a training loop, when a model trains but underperforms, or when a metric looks suspiciously good or suspiciously bad - [Choosing What To Fix](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-choosing-what-to-fix) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-choosing-what-to-fix` Use when deciding what to work on next on an ML project, when a model is underperforming and the cause is unclear, when setting up train dev and test splits, or when tempted to collect more data or build a bigger model - [Evaluating Llm Systems](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-evaluating-llm-systems) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-evaluating-llm-systems` Use when building evals for an LLM feature or agent, when setting up an LLM-as-judge, when prompt changes cannot be verified as improvements, or when a RAG or agent pipeline works on examples but fails in production - [Becoming One With The Data](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-becoming-one-with-the-data) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-becoming-one-with-the-data` Use when starting any ML task, before writing a model or training loop, when inheriting an unfamiliar dataset, when eval results are surprising in either direction, or when suspecting label noise, duplicates, leakage, or contamination - [Regularizing A Model](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-regularizing-a-model) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-regularizing-a-model` Use when a model fits the training set but generalizes poorly, when validation loss rises while training loss falls, when deciding between dropout weight decay augmentation or more data, or when choosing when to stop training - [Using Ml Superpowers](https://agentstack.voostack.com/l/skill-umaraslam66-ml-superpowers-using-ml-superpowers) — Skill · Free · security-reviewed — `agentstack add skill-umaraslam66-ml-superpowers-using-ml-superpowers` Use when starting any machine learning, model training, fine-tuning, or evaluation task - establishes which ML skill to invoke before writing model code --- Seller on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Install any with `agentstack add `.