deep-learning-forecasting
deep-learning-forecasting is a Time series & forecasting skill for AI agents, published by skforecast in the skforecast repository on GitHub. Skillspace rates deep-learning-forecasting D (64/100) and it passed the safety scan; a judge model has also reviewed it.
Forecasts time series using recurrent neural networks (RNN, LSTM, GRU) with ForecasterRnn and the create_and_compile_model helper. Covers model architecture, training, and multi-series deep learning. Use when the user wants to use deep learning / neural networks for time series forecasting.
- Grade
- D
- Quality
- 64 / 100
- Safety
- Passed
- GitHub stars
- 1,512
Placed #4 of 6 in the judged category final for Time series & forecasting.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 82 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- BSD-3-Clause
- Adoption
- Adopted by 1 other repositories, in 0 collections
- Scope
- Vendor-specific: built around one product. Using skforecast's public ForecasterRnn API for forecasting
Judge review
Placed #4 of 6 in the judged category final for Time series & forecasting.
- Trigger
85 85 - Instructions
88 88 - Specificity
90 90 - Safety
80 80 - Disclosure
90 90 - Maintenance
70 70
Solid architecture reference and stop-conditions table for RNN forecasting, cleanly cross-linked to sibling skills for the steps before and after it.
Not checked yet
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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