Results for “bat”

抓取知乎收藏夹与文章正文为 Markdown，支持图片本地化、断点续传及写入 Obsidian 知识库。

Read and write Google Sheets spreadsheets using the gws CLI, including batch updates, creation, and data retrieval.

Creates, edits, converts, and automates LibreOffice Calc spreadsheets in ODS format, including formulas, charts, and batch processing.

Creates, edits, converts, and automates spreadsheet workflows using LibreOffice Calc, including formulas, charts, and batch processing.

Build Cloudflare D1 schemas and queries with Drizzle ORM, including migrations, relations, and batch operations.

For analysis/task/review agents using a Professional Skill on batch, stream, warehouse, lineage, replay, or data quality; not for transactions without distributed-data impact.

Analyze single-cell RNA-seq data using Scanpy, including quality control, normalization, clustering, marker gene identification, and visualization.

Generates Python code to batch-translate the English column of tab-separated CSV files while preserving the original Chinese column and output format.

Grades and classifies evaluation batch results, applying exclusions, diagnosing failure modes, computing pass rates, and generating summary tables for papers.

Generate production-ready Dataverse SDK solutions with architecture recommendations, data models, and implementation code for common business use cases.

Build real-time streaming applications with the Azure Event Hubs SDK for Java, including sending and receiving events, batch processing, and production-ready event processors.

Diagnoses and resolves slow Qdrant indexing and data ingestion by optimizing batching, sharding, HNSW parameters, and payload indexing strategies.

Interact with Cat Town, a Farcaster-native game world on Base, covering KIBBLE staking, world state, fishing drops, competitions, raffles, boutique, gacha, and tokenomics.

Provides deep generative models for single-cell omics analysis, including probabilistic batch correction, transfer learning, differential expression, and multi-modal integration.

dbt (data build tool) transforms data in your warehouse using SQL SELECT statements. Learn project setup, models, tests, documentation, incremental materializations, and integration with data warehouses like PostgreSQL, BigQuery, and Snowflake.

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.

Automate SEO research with Ahrefs — analyze backlink profiles, research keywords, track domain metrics history, audit organic rankings, and perform batch URL analysis through the Composio Ahrefs integration.

Rapidly classify malware samples against known family signatures using YARA rules, covering rule writing, scanning, and integration with analysis pipelines.

Access microscopy images and metadata via the OMERO Python API: retrieve datasets, analyze pixels, manage ROIs and annotations, and batch-process for high-content screening workflows.

Provides battle-tested PyTorch training recipes for LLMs, vision, diffusion, and biomedical domains, covering training loops, optimizer selection, LR scheduling, mixed precision, and debugging.

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.

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.

Design data systems by understanding storage engines, replication, partitioning, transactions, and consistency models. Use when the user mentions "database choice", "replication lag", "partitioning strategy", "consistency vs availability", "stream processing", "ACID transactions", "eventual consistency", or "LSM tree vs B-tree". Also trigger when choosing between SQL and NoSQL, designing data pipelines, or debugging distributed system consistency issues. Covers data models, batch/stream processing, and distributed consensus. For system design, see system-design. For resilience, see release-it.