3. Data, Science & AI

Analyzes database query performance to identify bottlenecks and optimize SQL execution for improved application efficiency.

Automates machine learning hyperparameter tuning using grid search, random search, or Bayesian optimization with code generation and performance metrics.

Validates production readiness of Vertex AI Agent Engine deployments across security, performance, compliance, and best practices with weighted scores and recommendations.

Executes NLP for text analysis including sentiment, keyword extraction, and topic modeling.

Validates ethical implications and fairness of AI/ML models and datasets, providing bias detection and mitigation recommendations for responsible AI deployment.

Evaluates machine learning models using key metrics including accuracy, precision, recall, and F1-score for performance analysis.

Enables speech-to-text transcription workflows for pre-recorded audio and batch processing via Deepgram's AI service.

Tracks and analyzes Cursor code editor usage metrics, delivering insights via analytics dashboards and reports.

Generates usage analytics and cost reports for Kling AI, tracking generation patterns and providing dashboard visualizations.

Executes regression analysis on datasets, generating linear/polynomial models with validation and performance metrics.

Logs and tracks machine learning experiment metrics, parameters, and artifacts using Weights & Biases (wandb) for model training and analysis.

Executes clustering algorithms (K-means, DBSCAN, hierarchical) on datasets for group identification and data structure analysis, with validation and metrics.

Validates AI/ML models and datasets for bias, fairness, and ethical compliance to ensure responsible AI deployment.

Automates anomaly detection in data analytics workflows. Activates on triggers like 'anomaly detector' or 'anomaly' to identify unusual patterns.

AI-powered CLI for image/video analysis, OCR, real-time web search, and GitHub code exploration via z.AI API.

Optimizes Lindy AI agent response times and throughput by reducing latency and improving performance.

Automates creation of Apache Flink jobs for stream processing data pipelines, enabling efficient data pipeline management.

Manages mixed precision training operations for machine learning models, optimizing performance and memory usage during training.

Tracks and manages AI/ML model versions, lineage, performance, and deployment using model registry and MLflow integration.

Builds production AI agents using Google's Agent Development Kit with React patterns and multi-agent orchestration for complex task execution.

Optimizes LLM prompts to reduce token usage, lower costs, and improve response quality through concise rewrites.

Recommends appropriate chart types for data visualization based on input data characteristics and analysis goals.

Provides database schema patterns for social graphs, e-commerce, content publishing, and multi-tenancy with Row Level Security (RLS) policies.

Builds reusable scripts to fetch, process, and enrich data from Hugging Face API for AI/ML workflows and automation.