page updates

Author: NathanLuckock

full_stack.qmd

@@ -15,34 +15,31 @@ subtitle: "Backend Systems & Architecture"
 
 ### System Architecture:
 - **Microservices**: Scalable systems using containerized microservices
-- **API Design**: RESTful and WebSocket APIs for real-time communication
+- **API Design**: FastAPI's and WebSocket APIs for real-time communication
 - **Database Optimization**: Efficient query patterns and indexing
 - **Load Balancing**: Systems to handle high-volume data streams
 
 ### DevOps & Deployment:
 - **Docker**: Containerizing applications for consistent deployment
 - **CI/CD**: Automating build, test, and deployment processes
 - **Monitoring**: Comprehensive monitoring and logging systems
-- **Infrastructure**: Managing cloud and on-premises infrastructure
 
 ### Frontend Integration:
 - **Data Visualization**: Dashboards and charts for real-time data
-- **User Interface**: Intuitive interfaces for industrial operators
 - **Real-time Updates**: WebSocket connections for live data
 - **Responsive Design**: Interfaces for different devices and screens
 
 ### Technical Stack:
-- **Backend**: Python, FastAPI, SQLAlchemy, PostgreSQL, Redis
-- **Frontend**: HTML, CSS, JavaScript, Chart.js, WebSocket
+- **Backend**: Python, FastAPI, SQL, Redis, Docker, Kubernetes, MQTT
+- **Frontend**: HTML, CSS, JavaScript, React, Next.js
 - **DevOps**: Docker, Git, CI/CD, monitoring tools
-- **Data Processing**: Pandas, NumPy, real-time streaming
-- **Communication**: MQTT, REST APIs, WebSocket
+- **Communication**: MQTT, Fast APIs, WebSocket
 
 ### Key Projects:
-- **Industrial Data Pipeline**: End-to-end system for sensor data
+- **Industrial Data Pipeline**: End-to-end systems for data extraction and processing
 - **Real-time Dashboard**: Web interface for monitoring processes
 - **API Gateway**: Centralized API management
-- **Data Processing Engine**: High-performance data analysis system
+- **Data Processing Engine**: High-performance data analysis systems
 
 ### Performance & Security:
 - **Query Optimization**: Reducing query times for large datasets

ml.qmd

@@ -21,40 +21,31 @@ subtitle: "AI Development"
 
 ## Planned Portfolio Projects
 
-### Project 1: Predictive Maintenance System
-- **Objective**: ML model to predict equipment failures
-- **Data**: Historical sensor data from industrial equipment
-- **Techniques**: Time-series analysis, classification algorithms
-- **Tools**: Python, scikit-learn, pandas
-
-### Project 2: Anomaly Detection
-- **Objective**: Unsupervised learning system for sensor readings
-- **Data**: Real-time sensor data streams
-- **Techniques**: Isolation Forest, One-Class SVM, Autoencoders
-- **Tools**: Python, TensorFlow
-
-### Project 3: NLP for Technical Documentation
-- **Objective**: NLP system to analyze technical documents
-- **Data**: Technical manuals, bug reports, documentation
-- **Techniques**: Text classification, sentiment analysis
-- **Tools**: Python, NLTK, spaCy
-
-### Project 4: Computer Vision for Quality Control
-- **Objective**: Computer vision system for quality inspection
-- **Data**: Images of manufactured products
-- **Techniques**: Convolutional Neural Networks, object detection
-- **Tools**: Python, OpenCV, TensorFlow
-
-### Project 5: Reinforcement Learning for Process Optimization
-- **Objective**: RL agent to optimize industrial processes
-- **Data**: Process control data and performance metrics
-- **Techniques**: Q-learning, policy gradients
-- **Tools**: Python, Gym, TensorFlow
+### Project 1: Predictive Modeling with Historical Time-Series Data
+- **Objective**: ML model (LSTM/XGBoost) that analyzes historical data to forecast future trends
+- **Application**: Industrial output, resource demand, or financial metrics forecasting
+- **Features**: Dynamic visualizations and real-time predictions for operational decision-making
+- **Techniques**: LSTM, XGBoost, time-series analysis
+- **Tools**: Python, LSTM, XGBoost
+
+### Project 2: AI-Powered Script-to-Video Generation Pipeline
+- **Objective**: Comprehensive pipeline that transforms written scripts into short video content
+- **Technology**: LLMs, image/video APIs, and voice synthesis
+- **Features**: Advanced AI coordination across language processing, media generation, and rendering
+- **Techniques**: LLM integration, video generation, voice synthesis
+- **Tools**: Python, LLM, Video Generation APIs
+
+### Project 3: Natural Language Agent for Structured Data Analysis
+- **Objective**: Intelligent AI agent that interprets natural language queries and analyzes data sources
+- **Application**: Uploaded or connected data sources (e.g., CSVs)
+- **Features**: Leverages LLM technology to provide accurate, human-readable answers and visual insights
+- **Techniques**: LLM integration, natural language processing, data analysis
+- **Tools**: Python, LLM, Data Analysis libraries
 
 ## Skills:
 - **Supervised Learning**: Classification, regression, time-series forecasting
 - **Unsupervised Learning**: Clustering, anomaly detection
-- **Deep Learning**: Neural networks, CNNs, RNNs
+- **Deep Learning**: Neural networks, CNNs, RNNs, LSTM
 - **Model Deployment**: Docker containers, API development
 - **Data Engineering**: Feature engineering, data preprocessing