Plugins

7 plugins

Dotnet Aspnetcore

ASP.NET Core web development skills including middleware, endpoints, real-time communication, and API patterns.

4 skills · plugin

Azure Web PubSub Toolkit

For developers building real-time messaging apps with Azure Web PubSub using JavaScript and Python.

3 skills · plugin

Full-Stack Backend Platforms

For developers building backends with Convex, Firebase, or Django, covering schema design, real-time features, and deployment.

10 skills · plugin

Build Gemini Live API App

Build real-time, bidirectional streaming applications with the Gemini Live API, covering WebSocket-based audio/video/text streaming and function calling.

4 skills · plugin

@pranavnagrecha

AwesomeSalesforceSkills

1,034 grounded Salesforce skill packages, 48 run-time agents and 67 slash commands, reached through 12 lightweight router skills instead of a flat index.

94 skills · plugin

Kanzlei Allgemein

Kanzlei-Allgemein-Plugin (fusioniert mit Cowork): edles Kommandocenter Mandatsannahme/GwG Klage/Replik Vertrag Rechtsprechung Handelsregister beA-Journal Rechnung UStVA Fristenbuch Timesheet RVG Versand-Vor-Check Posteingang Mandantenakte Mahnwesen Tagesbrief Geburtstage Weihnachtskarten.

4 skills · plugin

@alirezarezvani

Business Operations

Internal BizOps domain. v2.8.0 ships 7 skills: orchestrator + process-mapper (BPMN/bottleneck/cycle-time, Lean+TOC) + vendor-management (scorecard+SLA+3rd-party risk, NIST SP 800-161/ISO 27036) + capacity-planner (Erlang-C queueing math for ops teams, NOT engineering) + internal-comms (ADKAR+Kotter 8-step, NOT marketing) + knowledge-ops (SOP+runbook+KB hygiene with 5W2H, context: fork) + procureme

3 skills · plugin

Results for “time”

22 skills

Reads and preprocesses 5-minute stock candlestick CSV data, then clusters the time series using tslearn's TimeSeriesKMeans, including data cleaning, percentage change calculation, model training, saving, and representative sample extraction.

085-aeon-556c1766

Provides guidance on using the Aeon library for time series forecasting, covering model selection, implementation, and evaluation.

Provides scikit-learn compatible algorithms for time series machine learning, including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search.

Performs time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search using the aeon toolkit.

Runs time series machine learning tasks—classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search—using the scikit-learn compatible aeon toolkit.

200-aeon-e7807df1

Guides feature extraction and preprocessing for time series data using aeon transformers, covering collection and series transformers with code examples.

More results

Fit statistical models (OLS, GLM, ARIMA, mixed models) with detailed diagnostics, residuals, and inference for econometrics and time series analysis.

30.2k · bundle

leandrobenjaminl

time-series-analysis

Analiza series temporales: tendencia, estacionalidad y pronóstico con Prophet, statsmodels y ML, incluyendo descomposición, tests de estacionariedad y evaluación contra baselines.

Perform time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search using a scikit-learn compatible Python toolkit.

30.2k · bundle

164-aeon-39ccf444

Predict continuous values from temporal sequences using aeon's time series regressors, covering convolutional, deep learning, distance-based, feature-based, hybrid, interval-based, and shapelet-based approaches.

azure-ai-anomalydetector-java

Detect anomalies in time-series data using the Azure AI Anomaly Detector SDK for Java, with support for univariate and multivariate analysis, model training, and inference.

Analyze RNA velocity in single-cell RNA-seq data with scVelo, estimating cell state transitions from unspliced/spliced mRNA dynamics, inferring trajectory directions, computing latent time, and identifying driver genes.

Measures the trade-off between computation time and energy consumption in mobile edge computing by computing a weighted sum of the two objectives, given system configuration parameters and per-user task characteristics.

hf-cloud-sagemaker-deployment-planner

Plans and coordinates the deployment of a model to Amazon SageMaker AI, selecting the appropriate pathway (real-time, serverless, async, batch, or Bedrock CMI) based on model type, traffic, latency, and cost constraints.

earth2studio-create-prognostic

Create Earth2Studio prognostic model wrappers that time-step weather forecasts forward, with triple-inheritance classes, tests, and documentation.

orchestra-research

rwkv-architecture

Use RWKV, a linear-time RNN-Transformer hybrid, for efficient long-context inference and training with constant memory usage.

10.4k · bundle

Evaluates the naturalness, speaker similarity, and real-time synthesis speed of a Mandarin speech cloning system across diverse practical application scenarios.

phoenix-observability

Self-hosted observability platform for LLM applications, providing tracing, evaluation, datasets, experiments, and real-time monitoring to debug and improve AI systems.

orchestra-research

weights-and-biases

Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B.

10.4k · bundle

Estimate cell state transitions from unspliced/spliced mRNA dynamics using scVelo, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data.

30.2k · bundle

nemo-mbridge-multi-node-slurm

Convert single-node PyTorch distributed scripts into multi-node Slurm sbatch jobs and debug common multi-node failures, covering srun-native and torch.distributed approaches, container setup, NCCL timeouts, and interactive allocation.

Evaluates computational throughput and real-time efficiency of embedded CPU and GPU platforms by measuring peak FLOPS via a matrix rotation kernel and assessing inference latency and power consumption on a robotic vision pipeline.