Results for “process-execution”
17 skills
tradermonty trade-performance-coach
Reviews closed trades, partial exits, and monthly trade aggregates for process adherence, risk discipline, execution quality, and evidence-based trading behavior patterns.
2.3k · bundle
lingxling polars
High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.
253 · bundle
nimoqup046-collab polars
Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for faster pandas-style workflows.
2
composiohq pdf-co-automation
Automates PDF.co operations through Composio's toolkit via Rube MCP, including tool discovery, connection management, and execution.
66.9k
jorcan polars
Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for fast in-memory analysis and pandas migration.
0 · bundle
phoroth polars
Process in-memory tabular data with a fast, expression-based DataFrame library that supports lazy evaluation, parallel execution, and Apache Arrow semantics.
3
More results
k-dense-ai polars
Process data with high-performance DataFrames using Polars' expression-based API, lazy evaluation, and parallel execution for ETL, analytics, and pandas migration.
30.2k · bundle
lingxling matlab
Numerical computing with MATLAB and GNU Octave for matrix operations, data analysis, visualization, and scientific computing, including script execution and syntax guidance.
253 · bundle
inference-sh python-executor
Execute Python code in a safe sandboxed environment with 100+ pre-installed libraries for data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, and automation.
584
rbutinar fabric-sp-run
Execute Stored Procedures on a Fabric Warehouse
0
orchestra-research ray-data
Process large-scale ML datasets with distributed streaming execution across CPU/GPU, supporting Parquet, CSV, JSON, images, and integration with PyTorch, TensorFlow, and Ray Train.
10.4k · bundle
lucaspmarie-a11y polars
Process in-memory datasets with Polars' expression API, lazy evaluation, and parallel execution, including pandas migration patterns and I/O for CSV, Parquet, and JSON.
5
mukul975 implementing-siem-correlation-rules-for-apt
Detect APT lateral movement by chaining Windows authentication events, process execution telemetry, and network connection logs across hosts using Splunk SPL and Sigma rule format.
24.6k · bundle
qhjqhj00 ray-data
Process large ML datasets in parallel across CPU or GPU clusters, with streaming execution, multi-format I/O, and integration with Ray Train, PyTorch, and TensorFlow for batch inference and preprocessing pipelines.
3 · bundle
tianhao909 ray-data
Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.
1 · bundle
qcmuu ray-data
Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.
0 · bundle
alterlab-ieu alterlab-dask
Scales pandas/NumPy workflows beyond memory with Dask distributed computing — parallel DataFrames, arrays, delayed task graphs, and cluster execution. Use when existing pandas/NumPy code must run on larger-than-RAM data or across clusters, for parallel file processing, distributed ML, or integration with existing pandas code. For out-of-core analytics on a single machine prefer vaex; for in-memory speed prefer polars. Part of the AlterLab Academic Skills suite.
60 · bundle