ML in Data & Analytics

Build, debug, and optimize Claude API applications with caching and model migration support.

Create and manage scalable REST API endpoints for LLMs and ML models.

Build vector search indexes and semantic search applications on Databricks.

Generate a complete ontology layer and semantic models from your Snowflake schema.

Set up and run AI evaluation pipelines with MLflow scorers and automated prompt optimization.

Generate realistic test datasets in Parquet, JSON, CSV, or Delta format at any scale.

Create knowledge assistants and supervisor agents for document Q&A and multi-agent workflows.

Design and implement ML operations for model promotion, CI/CD, monitoring, and governance.

Manage LLM provider credentials and integrations in Arize for evaluators.

Create annotation schemas and manage human review workflows in Arize.

Work with astronomical data using Python's core astronomy library for coordinates, units, and FITS files.

Search scientific papers and extract structured experimental data like methods, results, and sample sizes.

Classify, forecast, and detect anomalies in time series data using specialized machine learning algorithms.

Work with annotated data matrices and .h5ad files for single-cell analysis.

Test your understanding of AI Engineering from Scratch course phases.

Build knowledge graphs from documents and search them with natural language queries.

Analyze customer accounts to predict churn risk and identify expansion opportunities.

Analyze investment opportunities by evaluating whether a project creates new order or merely shifts existing structures.

Analyze earnings reports and financial documents with deep insights.

Find supply chain inefficiencies and arbitrage opportunities across global industries.

Autonomously research, benchmark, and implement performance optimizations with production-ready pull requests.

Find and discover NVIDIA-related skills for GPUs, CUDA, Jetson, and other NVIDIA products.

Accelerate pandas DataFrames with NVIDIA GPU computing for large-scale data processing.

Run deep research queries against a local NVIDIA AI-Q Blueprint server.

Route research tasks to the right empirical analysis skill from a catalog of 1,150 options.

Run a complete econometric analysis pipeline with regression, causal inference, and publication-ready tables.

Build publication-ready regression tables, diagnostics, and causal analyses in Python.

Run a complete econometric analysis pipeline from data cleaning to publication-ready tables and figures.

Attack ML models, craft adversarial examples, and solve AI-based CTF challenges.

Analyze global markets, forex, commodities, and economic indicators to assess trading conditions.

Submit protein sequences for automated lab testing and validation experiments.

Review and critique your ML models with fact-based feedback and iterative refinement.

Classify, forecast, and analyze temporal data with specialized time series machine learning algorithms.

Verify numeric claims in manuscripts match actual analysis outputs within tolerance.

Set up AI Runway on Azure Kubernetes Service from cluster to running model.

Search, transcribe speech, and extract text from documents using Azure AI.

Build Node.js backend AI apps with text and image generation models.

Optimize your CLAUDE.md file for clarity, efficiency, and maintainability.

Find new Japanese NLP GitHub repositories missing from awesome-japanese-nlp-resources lists.

Research current challenges and solutions in Japanese natural language processing.

Analyze current trends in Japanese natural language processing with web research and curated datasets.

Search libraries, models, and datasets for Japanese natural language processing.

Remove PCR primer sequences from amplicon sequencing reads using samtools.

Generate counterfactual explanations and trust scores to understand AI model decisions.

Detect and mitigate bias in machine learning models with fairness metrics and compliance reports.

Explain individual AI predictions for tabular, text, and image data.

Create and configure MATLAB experiments to sweep parameters and compare configurations.

Import PyTorch, ONNX, and Keras models into MATLAB as dlnetwork objects.

Find the right AI model for your task with capabilities and cost comparisons.

Extract sparse ideas, dense ideas, and experimental logs from research papers for benchmarking.

Search and download academic papers from arXiv without needing an API key.

Write LaTeX ML/AI review articles with verified citations for arXiv.

Turn frozen research plans into reproducible, auditable experiment code with data leak prevention.

Execute autonomous multi-step research and generate detailed, cited reports.

Deploy and manage generative AI models and ML workflows on SAP's enterprise cloud platform.

Generate a daily AI news digest from top tech sources and blogs.

Apply AI and semiconductor supply-chain analysis to evaluate stock ideas and market outlook.

Build self-improving AI agents using 9 reinforcement learning algorithms.

Calculate delta, gamma, theta, vega, and implied volatility for options.

Train custom LoRAs for WAN video models and Z-Image with local or cloud setup.

Identify where money is flowing across US market sectors each trading day.

Render interactive financial charts with technical indicators and market data.

Manage GPU instances, volumes, and billing on Vast.ai.

Manage GPU instances, volumes, and serverless endpoints on Vast.ai.

Migrate embedding models in Qdrant without downtime or data loss.

Manage machine learning workloads on the Inspire platform via command-line interface.

Train custom small language models using knowledge distillation and production data.

Test trading strategy parameters and generate performance heatmaps.

Predict protein, nucleic acid, and small-molecule complex structures from FASTA sequences.

Generate backtest statistics for a stock symbol using an EMA crossover strategy.

Predict 3D binding poses for small molecules in protein structures.

Predict protein structures for single proteins and complexes using AlphaFold2.

Compare multiple trading strategies side-by-side with performance stats.

Generate a complete backtesting script for trading strategies with data, signals, and performance charts.

Generate publication-ready statistical code and tables for medical research papers.

Find and explore academic papers, citations, and authors using Semantic Scholar's research corpus.

Render interactive financial charts with technical indicators and market data.

Deploy AI models to resource-constrained hardware using MATLAB and Simulink.

Extract method details, innovations, and results from 3D Gaussian Splatting research papers.

Search and verify citations for research papers with accuracy checks.

Audit and verify experimental evidence for research papers with reproducibility checks.

Generate and audit publication-ready plots for computer science and machine learning papers.

Audit whether a paper's evaluation actually measures what it claims to measure.

Audit research paper tables and images for statistical inconsistencies and data integrity issues.

Extract keywords and patterns from converted text recordings.

Build and optimize Snowflake data pipelines, SQL queries, and AI-powered applications.

Create and query Databricks Genie Spaces for natural language SQL exploration.