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TAM-DS/README.md

Tracy Manning

Machine Learning Engineer | AI Systems Architect

πŸš€ I build machine learning systems that scaleβ€”taking projects from raw data to deployed models in production. From classical ML pipelines to cutting-edge quantum experimentation, I design architectures that deliver measurable performance gains and real-world impact

Core Specialties

  • ML Engineering: End-to-End pipelines (data prep β†’ model training β†’ deployment)
  • Cloud Infrastructure: Oracle, AWS, Azure, & GCP
  • Applied AI: Generative AI, LangChain, Vector search, AI agents
  • Quantum ML (Experimental): Prototype circuits & simulations for future-ready ML

Database & Analytics Platforms

ANSI SQL Certified - Universal Database Compatibility Comprehensive SQL expertise enabling seamless work across traditional databases (MySQL, PostgreSQL, SQLite, Oracle, SQL Server) and modern big data platforms (Spark SQL, Hive SQL, Snowflake, Google BigQuery, Azure Synapse).

Featured Projects (in progress)

  • Python Trading Algo β€” A working trading algorithm using simple signal logic (β†’) πŸ”— Github
  • Quant11Python β€” Quantum Teleportation Prototype (β†’) πŸ”— Github

SQL / Big Query Projects

  • Exploratory Data Analysis (EDA) (β†’) πŸ”— GitHub being updated
  • Data Warehouse (β†’) πŸ”— GitHub being updated

πŸš€ Data to Decisions: Portfolio of Executive-Grade Intelligence

Interactive dashboards that transform complex data into strategic advantage.

Here are three projects that showcase the full spectrum of my portfolio:

Tesla's Path To Mars: Infrastructure Requirements 2024-2035 (β†’) πŸ”— Tesla's Path To Mars Dashboard – Tableau

πŸ”ŒπŸ“Š Data Sources: Self-compiled analysis sourcing Tesla financials, SpaceX mission data, and space communication specs through SQL, Python, and Tableau.

πŸ” Key Insights

  • Communication Challenge: Earth's 0.001ms latency vs Mars' 4.28-minute delays require fully autonomous systems
  • Data Explosion: Operations must scale from 50TB daily to 1,500TB+ for Mars colonies
  • Investment Reality: Current $2.5B β†’ Required $80B infrastructure investment
  • Technology Readiness: Must achieve Level 9 (fully operational) before 2029 launch window
  • The Valley of Death: 2028-2031 validation period when proven Earth tech needs Mars validation
  • Timeline Modeling: Optimus robot deployment phases (2024-2030)
  • Communication Complexity Analysis: Autonomous system dependency mapping
  • Financial Projections: Infrastructure investment scaling ($2.5B β†’ $80B)
  • Risk Assessment: Mission criticality analysis

πŸ’‘ Impact

This analysis reveals why Tesla's Earth infrastructure investments aren't just about terrestrial operations - they're building the foundation for humanity's multi-planetary future. Every autonomous system, every data processing capability, and every operational efficiency gain directly impacts the probability of Mars colony survival.

Data Center Revolution: AI, Sustainability & Scale (2018–2025) (β†’) πŸ”— Data Center Revolution Dashboard – Tableau

πŸ”ŒπŸ“Š Data Source: Self-compiled dataset to change how people think about AI efficiency.

πŸ” Key Insights

  • Explored the explosive rise of AI infrastructure vs. sustainability solutions β€” 16x faster growth.
  • Visualized the Cooling Revolution (PUE dropping 3.0 β†’ 1.2)
  • Cloud Computing Market 3.5x Gold Rush
  • Network Infrastructure in Tbps increases in both speed evolution and scale perspective.
  • And the emerging frontier of space-based data centers. Led by SpaceX, Thales Alenia Space, and CloudConstelation

πŸ’‘ Impact

  • Built a 7-slide interactive data story that reimagines the future of computing infrastructure.
  • Positioned complex metrics as a manifesto for humanity’s computational future.

Texas AI Infrastructure Analysis: Smart Contract Automation Opportunity (β†’) πŸ”— Smart Contract Automation Opportunity Dashboard - Tableau

πŸ”ŒπŸ“Š Data Source: Self-compiled dataset proving smart contract automation delivers 4,000%+ ROI, 99.7% faster settlements, and measurable ESG impact.

πŸ” Key Insights

  • Settlement Speed Reduction: 78 days β†’ 47 minutes (99.7% improvement)
  • Average ROI: 4,000%+ across all analyzed companies
  • Cost Savings: $400-1,900 per transaction through automation
  • Environmental Impact: Correlation analysis between renewable energy adoption and operational efficiency

    Companies Included

  • Google Cloud Texas
  • Microsoft Azure Houston
  • Meta AI Infrastructure
  • Tesla Gigafactory Texas
  • NVIDIA DGX Centers
  • Amazon AWS Dallas
  • Stream Data Centers Houston
  • Serverfarm Houston
  • Apple Manufacturing Houston
  • Oracle Cloud Austin

πŸ’‘ Impact

  • Operational Imperative: 4,000%+ ROI demonstrates automation is no longer optional
  • Competitive Advantage: 99.7% settlement speed improvement enables new service models
  • ESG Compliance: Carbon efficiency gains support sustainability initiatives
  • Risk Mitigation: Automated processes reduce human error and operational exposure

πŸ› οΈ Technical Stack

  • Python (Pandas, Numpy): Data processing, calculations, and analysis pipelines
  • TensorFlow & PyTorch: Predictive modeling
  • SQL (ANSI Certified): Database queries and data transformation
  • Apache Spark: Distributed processing
  • Tableau: Interactive dashboard development and visualization

πŸ”§ Advanced Analytics Portfolio

(β†’) πŸ”— Tableau Public | Dashboards that Redefine What Data Can Do

πŸ… Industry Certifications (Being Updated)

www.linkedin.com/in/tracy-manning-ai-ml

azure bash bootstrap css3 docker elasticsearch gcp git graphql hadoop hive html5 kafka kubernetes linux matlab mongodb mssql mysql pandas postgresql python sass scikit_learn seaborn selenium sqlite tensorflow




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