Plugins

1 plugin

Results for “datasets”

18 skills
More results
agentskillexchange
Apify Actor Runner
Runs Apify cloud actors for structured web scraping and exports datasets to S3, with input schema validation and webhook notifications.
28
schattenspiegel
Pyarrow Python
Write, review, debug, test, or optimize Python code using PyArrow arrays, schemas, tables, compute kernels, datasets, Parquet, and Arrow IPC.
0 · bundle
nvidia
Cupynumeric Parallel Data Load
Load sharded datasets (npy, Parquet, HDF5, raw binary) into distributed cuPyNumeric arrays using manual partitioning and Legate task launches.
2.2k · bundle
muratcankoylan
Book Sft Pipeline
Convert books into supervised fine-tuning datasets and train style-transfer models that replicate an author's voice.
16.9k · bundle
neuralblitz
Big Data
Designs and implements big data architectures, processes large-scale datasets with distributed systems, and optimizes data pipelines for throughput using Hadoop, Spark, and cloud platforms.
1
lingxling
Pysam
Read, write, and analyze genomic datasets including SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences using a Pythonic interface to htslib.
253 · bundle
lingxling
Lamindb
Manages biological datasets and models with LaminDB, covering setup, artifact registration, querying, lineage tracking, validation, ontology annotation, collections, branches, storage, and workflow integrations.
253 · bundle
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
antigravity
Polars
Provides a fast in-memory DataFrame library for datasets that fit in RAM, with lazy evaluation, parallel execution, and an Apache Arrow backend for ETL pipelines and analytics.
42.4k
k-dense-ai
Vaex
Process and analyze large tabular datasets (billions of rows) that exceed available RAM using lazy, out-of-core DataFrames with fast aggregations, visualization, and machine learning integration.
30.2k · 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