That's me, Lance Hester
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Connecting with folks on
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Submitting inventions to the
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Writing blogs posts on
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Agile/Scaled Agile FramEwork (SAFe)/SCRUM:JIRA, Project Management, Scrum Master/Engineer -
Artificial Intelligence (AI) Frameworks:Hugging Face, Keras, Langchain, PyTorch (Lightning), TensorFlow -
Artificial Intelligence (AI) Agent Frameworks:LangGraph, LlamaIndex, Model Context Protocol (MCP), Smolagents -
Cloud Platforms:Akamai/Linode, AWS,Azure, GCP -
Collaborative Software:Atlassian (Confluence), Google Docs, Microsoft 360, Miro, Slack -
CyberSecurity:Distributed Denial of Service (DDoS) (Flow Based Monitoring (FBM) - NetFlow, sFlow ) -
Data Engineering:Elasticsearch, Redis, SQL(MySQL, PostgreSQL, Snowflake), Supabase -
Deep Learning (DL):Convolutional Neural Networks (CNNs), Diffusion Models, Fine-Tuning, Generative Adversarial Networks, (GANs), Latent Space, Long Short-Term memory (LSTM), Model Compression (Knowledge Distillation, Pruning, and Quantization), Recurrent Neural Networks (RNNs), Transformers -
Development Operations (DevOps):Coverage, Continuous Integration/ Continuous Deployment (CI/CD), Julia Testing, Linux, Pytest, Ruff, uv -
Generative AI:Fine Tuning (LoRA Adapters), Large Language Models (LLM), Ollama, Retrieval Augmented Generation (RAG) -
Machine Learning (ML) / Data Science:Anomaly Detection of Time Series Data, Classification, Clustering (DBSCAN, K-means, K-nearest neighbors), Data Sampling, Dimensionality Reduction (Latent Spaces, Linear Discriminant Analysis (LDA) Principal Component Analysis (PCA)), Dropout, Exploratory Data Analysis, imblearn, Linear Regression, Natural Language Processing (NLP), Quantile Regression, Random Forests, Sentiment Analysis, SMOTE, Time Series Analysis, Tuning, XGBoost -
ML Frameworks:Flux.jl, Matplotlib, Numpy, Pandas, Seaborn, Scikit-learn -
ML Operations (MLOps):Docker, Kubernetes -
Observability:Langfuse, OpenTelemetry -
Programming Languages:Julia, MATLAB, Python, R -
Statistics:Correlations (Auto, Cross, Kendall, Pearson, Spearman), Hypothesis Testing, Interquartile Range (IQR and Modified IQR) analysis,Propensity Modeling -
Version Control:git, Github, Gitlab -
Web Analysis:Real User Monitoring (RUM) - mPulse -
Web Frameworks:FastAPI, Flask, Genie.jl, Gradio, Streamlit -
Wireless Sensor Networks:IEEE 802.15.4, Internet of Things (IoT), SmartGrid, ZigBee Networks
My public, open source projects can be found in these repositories. Give a project a star (⭐) if you liked it or if it was instructional for you!
| Project Name | Main Libraries/Tools | Cloud Service | App | DevOps Best Practices |
|---|---|---|---|---|
| Artificial Intelligence (AI) | ||||
| AI Model Compression: Knowledge Distillation, Pruning, and Quantization | CNN Deep Learning Github Fine-Tuning Knowledge-Distillation Jupyter Pruning Python PyTorch Quantization Tensors uv |
LinkedIn Learning Module | ||
| Model Context Protocol Servers | Docker Github Google Gemini Node.js NPM Python VS Code uv |
Adaptation of the MCP Crash Course For Python Developers | ||
| Hugging Face Agents Course | ChatOllama Embedding Model Github Gradio Hugging Face Jupyter LangChain Langfuse Langgraph LlamaIndex NLP Ollama OpenTelemetry Prompt Engineering Python RAG smolagents uv |
Gradio | Hugging Face Agent Course | |
| Predicting Media Channel Sales Using Deep Learning with Tensorflow and Keras (end-to-end) | AWS-ECS Docker FastAPI GIT Github HTML Jupyter Keras Linux Matplotlib Numpy Pandas Pytest Python Ruff Scikit-learn Tensorflow uv YAML |
AWS | FastAPI | Cloud Computing CI/CD (Github Actions) Containerization Data Validation Deep Learning Error Handling Linting Model Registry Model/Data Monitoring Data Validation Type Hinting |
| Retrieval Augmented Generation (RAG) Q&A Mechanism to Access User Guide Information - Loving My 2010 iPod Shuffle | ChatOllama Deep Learning FAISS Github Hugging Face Jupyter LangChain Llama3.2 NLP Prompt Engineering Pypdf Python RAG Streamlit Transfer Learning uv |
Streamlit | AI RAG LLM Learning Module | |
| Building a LSTM Neural Network Using PyTorch | Deep Learning Github Jupyter Lightning Long Short-Term Memory (LSTM) Python PyTorch TensorBoard TensorFlow uv |
Learning Module | ||
| Combination Encoder Decoder Tranformers to Summarize Documents with Text Clustering and Topic Modeling | Encoder Decoder Deep Learning Github HDBSCAN Hugging Face Jupyter Latent Space NLP Numpy Pandas Python Prompt Engineering SBERT Transformers UMAP uv |
AI Learning Module | ||
| Semantic Search Application (end-to-end) | AWS-ECS Docker FastAPI Github HTML Hugging Face Jupyter NLP Pytest Python Ruff Scikit-learn uv YouTube API |
AWS | FastAPI | Cloud Computing CI/CD (Github Actions) Containerization Data Validation Error Handling Linting Model Registry Model/Data Monitoring Data Validation Type Hinting |
| Visualizing Latent Spaces | Github Jupyter Keras Matplotlib MNIST Numpy Python Scikit-learn TensorFlow |
Learning Module for Review | ||
| Data Analysis | ||||
| COVID Social Distancing - Why the 10 Person Rule Mattered so Much | Calculus Github Julia Jupyter Matplotlib Statistics Visual Studio Code |
Learning Module for Technical Presentation | ||
| Time Series Cross Correlations | Github Julia Jupyter Matplotlib Statistics Visual Studio Code |
Learning Module for Technical Presentation | ||
| Law & Order Cambridge - Exploratory Data Analysis (EDA) of Cambridge, MA Crime Statistics | Github EDA Markdown R R-Markdown R-Studio Statistics |
Learning Module for Technical Presentation | ||
| Data Engineering | ||||
| Dev/DevOps | ||||
| UV Flask Web Application Demo (end-to-end) | Docker Github Pytest Python Ruff uv |
Flask | CI/CD (Github Actions) Containerization Data Validation Error Handling Linting Logging Model Registry Model/Data Monitoring Data Validation Type Hinting |
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| Introduction to MetaProgramming | Github Julia Jupyter Visual Studio Code |
Learning Module for Technical Presentation | ||
| Introduction2Julia - A Series of Julia Coded Notebooks Introducing the Julia Programming Language | Github Julia Jupyter Visual Studio Code |
Learning Module for Technical Presentation | ||
| Machine Learning (ML) / ML Operations (MLOps) | ||||
| Predict Bank Churn Using Neural Networks (NNs) | AUC-ROC Deep Learning Dropout Github imblearn Jupyter Keras Matplotlib Numpy Pandas Python Seaborn Scikit-Learn SMOTE TensorFlow uv |
Project from Post Graduate program in Artificial Intelligence and Machine Learning (PGAIML): Business Applications University of Texas at Austin Course | ||
| Machine Learning Bank Fraud Detection | FacetGrid Github Isolation Foret Jupyter Numpy Pandas Python Scikit-Learn Seaborn UV |
Learning Module for Practice/Review | ||
| Handling Imbalanced Data in Machine Learning Models | Github imblearn Jupyter Numpy Pandas Python Scikit-Learn SMOTE Tomek |
Learning Module for Practice/Review | ||
| Predict The Fare of a Taxi Ride in Chicago Illinois | Deep Learning Github Jupyter Keras Matplotlib Numpy Pandas Plotly Python TensorFlow |
Learning Module for Google: Machine Learning Crash Course | ||
| Binary Classifier - Predicting Deaths on the Titanic | AUC Confusion Matrix EDA Github GridSearchCV Jupyter Logistic Matplotlib Numpy Pandas Python ROC Seaborn Scikit-learn Statistics uv Visual Studio Code |
Learning Module for Technical Presentation | ||
| Time Series XGBoost Forecasting Megawatt Hour Usage Application (end-to-end) | AWS-ECS Cross Validation Docker EDA FastAPI Github HTML Jupyter Matplotlib NumPy Pandas Pytest Python Ruff Scikit-learn Time Series uv YAML |
AWS | FastAPI | Cloud Computing CI/CD (Github Actions) Containerization Data Validation Error Handling Linting Model Registry Model/Data Monitoring Data Validation Type Hinting |
| Regression Analysis Car MPG Project: Linear and Quantile Regressions in Julia Programming | Github Julia Jupyter Matplotlib R Scikit-learn Statistics Visual Studio Code |
Learning Module for Technical Presentation | ||
| Julia ML Project to Production Programming | Bash Shell Docker Github HTML Julia Jupyter Linux Matplotlib Scikit-learn Statistics Ubuntu Visual Studio Code |
Gene.jl | Learning Module for Technical Presentation | |
| Miscellaneous | ||||
| Generative AI: Introduction to Diffusion Models for Text Generation | Diffusion Models Fine-Tuning Github Google Gemini Hugging Face Masked Language Models (MLM) ModernBERT Natural Language Generation (NLG) Natural Language Processing (NLP) Python uv |
LinkedIn Learning Course Generative AI: Introduction to Diffusion Models for Text Generation | ||
| Python AsyncIO - How to Write Asynchronous Python Code | Github Python Ruff uv |
Learning Asynchronous Python Coding | ||
| Understanding Neural Network Matrix Algebra and Notation | Deep Learning Github Jupyter Neural Networks Matrix Algebra Python PyTorch Tensors uv |
Learning Module for Education and Meet-ups | ||
| Review of Python Classes and Instances Essentially Object Oriented Python (OOP) | Github Jupyter Python uv Visual Studio Code |
Learning Module for Practice/Review |
You've beenlanced! 😉