Use when implementing RL algorithms, training agents with rewards, or aligning LLMs with human feedback - covers policy gradients, PPO, Q-learning, RLHF, and GRPOUse when ", " mentioned.
9881 results
(74.2ms)
page 8 / 495
data-jupyter-python
0.00
Guidelines for data analysis and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.
# Liberty House Club **A Parallel Binance Chain to Enable Smart Contracts** _NOTE: This document is under development. Please check regularly for updates!_ ## Table of Contents -...
claudeception
0.00
|
Expert guidance for data analysis, visualization, and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.
deepchem
0.00
Molecular machine learning toolkit. Property prediction (ADMET, toxicity), GNNs (GCN, MPNN), MoleculeNet benchmarks, pretrained models, featurization, for drug discovery ML.
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.
data-analysis-sql
0.00
SQL for data analysis with exploratory analysis, advanced aggregations, statistical functions, outlier detection, and business insights. 50+ real-world analytics queries.
Organize and categorize files into logical structures. Creates folder hierarchies, renames files systematically, and consolidates related data.
csv-data-summarizer
0.00
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
XGBoost machine learning best practices for training, tuning, and deploying gradient boosted models. Use when writing, reviewing, or implementing XGBoost models for classification, regression, or...
Transfer learning, metrics optimization, and continuous improvement for AI-powered QE agents.
discover-ml
0.00
Automatically discover machine learning and AI skills when working with machine learning. Activates for ml development tasks.
gtars
0.00
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML...
gtars
0.00
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML...
Expert in data forensics, anomaly detection, audit trail analysis, fraud detection, and breach investigation
transparent-ui
0.00
Create standalone debugging interfaces that reveal the internal workings of complex systems through interactive visualization. Use when the user wants to understand how something works, debug...
Everyday data transformations using functional patterns - arrays, objects, grouping, aggregation, and null-safe access
self-learning-skills
0.00
Memory sidecar for agent work: recall before tasks, record learnings after tasks, review recommendations, optional backport bundles.