Results for “ai-models”
12 skills
microsoft Azure AI Document Intelligence Dotnet
Extract text, tables, and structured data from documents using Azure AI Document Intelligence SDK for .NET, with support for prebuilt and custom models.
2.7k
drnabeelkhan AI Engineer
Implements machine learning models, embeddings, and AI-powered features with ethical considerations, including model selection, integration, and monitoring.
2
oracle Oci
Design, operate, and troubleshoot OCI services including OKE, IoT, Functions, and Enterprise AI with OCI Generative AI models, agents, RAG, and cost estimation.
736 · bundle
k-dense-ai Transformers
Load pre-trained models from Hugging Face Hub, run pipeline inference, generate text, and fine-tune models on NLP, vision, audio, and multimodal tasks using the Transformers library.
30.2k · bundle
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oracle Enterprise AI
Navigate Oracle Cloud Infrastructure's Enterprise AI services: choose models, build agents with RAG and tools, estimate costs, secure access, and integrate with Oracle Database, APEX, and other platform services.
736 · bundle
rootcastleco AI Engineer
Build production-ready LLM applications, RAG systems, and intelligent agents with architecture design, model selection, and cost controls.
6
antigravity AI Engineer
Build production-ready LLM applications, advanced RAG systems, and intelligent agents with vector search, multimodal AI, and enterprise integrations.
42.4k
antigravity AI Product
Guides building production-grade AI features with LLM integration patterns, RAG architecture, prompt engineering, and cost optimization.
42.4k
k-dense-ai Deepchem
Predict molecular properties, train graph neural networks, and run drug discovery workflows using DeepChem's featurizers, models, and MoleculeNet benchmarks.
30.2k · bundle
microsoft Azure AI Document Intelligence TS
Extract text, tables, and structured data from documents using Azure Document Intelligence. Process invoices, receipts, IDs, forms, or build custom document models.
2.7k
k-dense-ai Molfeat
Convert chemical structures (SMILES or RDKit molecules) into numerical representations for machine learning using 100+ featurizers, including ECFP, MACCS, descriptors, and pretrained models like ChemBERTa.
30.2k · bundle
k-dense-ai Gtars
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 models, or fragment analysis in computational genomics and machine learning applications.
30.2k · bundle