Structuring Data Science with Jupyter Notebooks
"ArangoDB's use of Juypyter notebooks for its Data Science Suite is the perfect choice because this is an environment we are already comfortable using. It gives us all the flexibility we need to customize our dynamic AQL generation for GraphRAG and graph analytics jobs."
Schedule a Demo Today
to discover the power and flexibility of the ArangoDB Data Science Suite.
Read The
Whitepaper
on LLMs + Knowledge Graphs.
Orchestrate GraphML Processes
Streamline your data science workflows with Jupyter Notebooks. Our notebooks contain a template and roadmap to manage the entire GraphML workflow: managing compute resources, monitoring ML jobs, and handling containerization tasks. Focus on model development and tuning while we take care of the orchestration, ensuring a seamless and efficient GraphML process.
Simplified
Management
Abstract away the complexities of managing your ML tasks. With Jupyter Notebooks, you can monitor and control ML jobs seamlessly, focusing on what matters most—developing and tuning your models. Built-in tools for job tracking and resource usage visualization provide a straightforward path to deploying and maintaining your models.
Efficient, Automated Deployment
Handle containerization tasks with ease, ensuring that your ML models are deployed efficiently and reliably. Our platform supports Kubernetes, allowing for the seamless integration and orchestration of containerized ML jobs. This support is crucial for maintaining consistent performance across different environments and scaling resources dynamically based on workload demands.
Auto-Generate AQL from Natural Language
Set up dynamic AQL generation for GraphRAG. Leverage prompt engineering to create intelligent and adaptive queries, enabling real-time data interactions and natural language processing capabilities. This ensures that your queries are responsive and context-aware, providing accurate insights.
Schedule a Demo Today
to discover the power and flexibility of the ArangoDB Data Science Suite.
Read The
Whitepaper
on LLMs + Knowledge Graphs.