Notes on software engineering, working with AI, and what I'm picking up along the way.https://jongmin.me/https://jongmin.me/posts/omscs/aies/https://jongmin.me/posts/omscs/aies/Key AI ethics concepts from Georgia Tech OMSCS AIES (CS 6603): data and privacy, statistical literacy, fairness metrics, and bias mitigation.Thu, 13 Aug 2026 00:00:00 GMTAI EthicsOMSCSCS6603FairnessBiasAIhttps://jongmin.me/posts/omscs/kbai/https://jongmin.me/posts/omscs/kbai/Key knowledge-based AI concepts from Georgia Tech OMSCS KBAI (CS 7637): knowledge representation, reasoning strategies, learning, planning, and the ARC-AGI project.Mon, 11 May 2026 00:00:00 GMTKnowledge-Based AIOMSCSAICS7637ARC-AGIhttps://jongmin.me/posts/dev/team-ai-observations/https://jongmin.me/posts/dev/team-ai-observations/A few months into team-wide AI use, here are the patterns I'm seeing, and the question that keeps coming back about what should stay consistent across the team.Sat, 18 Apr 2026 00:00:00 GMTAIClaude CodeSoftware Engineeringhttps://jongmin.me/posts/dev/ai-dev-experience-after-job-change/https://jongmin.me/posts/dev/ai-dev-experience-after-job-change/Moving from a Copilot-only environment to a team that actively uses Claude Code: what changed and what I'm still figuring outSat, 14 Feb 2026 00:00:00 GMTSoftware EngineeringAIhttps://jongmin.me/posts/dev/understanding-claude-code-lifecycle/https://jongmin.me/posts/dev/understanding-claude-code-lifecycle/A walkthrough of Claude Code's execution lifecycle, from the moment you type a prompt to the final responseSat, 14 Feb 2026 00:00:00 GMTSoftware EngineeringAIClaude Codehttps://jongmin.me/posts/dev/windows-installer-offline-deployment/https://jongmin.me/posts/dev/windows-installer-offline-deployment/How I introduced a WiX-based Windows installer for deploying field software to air-gapped environments, and the unexpected challenges along the way.Tue, 10 Feb 2026 00:00:00 GMTSoftware Engineering.NETBest Practiceshttps://jongmin.me/posts/omscs/sdp/https://jongmin.me/posts/omscs/sdp/Key software engineering concepts from Georgia Tech OMSCS SDP (CS 6300): lifecycle models, UML, testing, Android development, and team collaboration.Fri, 19 Dec 2025 00:00:00 GMTSoftware EngineeringOMSCSUMLTestingAndroidAgileCS6300https://jongmin.me/posts/omscs/ai4r/https://jongmin.me/posts/omscs/ai4r/Key robotics AI concepts from Georgia Tech OMSCS AI4R (CS 7638): localization, planning, perception, control, and SLAM.Mon, 19 May 2025 00:00:00 GMTAIRoboticsOMSCSSLAMPath PlanningKalman FilterParticle Filterhttps://jongmin.me/posts/omscs/ml4t/https://jongmin.me/posts/omscs/ml4t/Key ML-for-trading concepts from Georgia Tech OMSCS ML4T (CS 7646): portfolio theory, signals, risk, and evaluation.Thu, 19 Dec 2024 00:00:00 GMTMachine LearningPortfolio TheoryML4TCS7646OMSCShttps://jongmin.me/posts/ml-stanford/8-unsupervised/https://jongmin.me/posts/ml-stanford/8-unsupervised/Explore core concepts of unsupervised learning, including K-means clustering, optimization strategies, and how anomaly detection systems are designed and evaluated.Tue, 09 Apr 2024 00:00:00 GMTMachine LearningUnsupervised LearningClusteringhttps://jongmin.me/posts/ml-stanford/7-decision-trees/https://jongmin.me/posts/ml-stanford/7-decision-trees/A complete guide to decision trees, covering entropy, information gain, one-hot encoding, regression trees, and ensemble methods like Random Forest and XGBoost.Wed, 03 Apr 2024 00:00:00 GMTMachine LearningDecision TreesXGBoosthttps://jongmin.me/posts/ml-stanford/6-ml-advice/https://jongmin.me/posts/ml-stanford/6-ml-advice/Learn how to make decisions, evaluate models, handle bias and variance, and manage real-world ML workflows with cross-validation, error analysis, and transfer learning.Mon, 01 Apr 2024 00:00:00 GMTMachine LearningModel EvaluationBest Practiceshttps://jongmin.me/posts/ml-stanford/5-nn-training/https://jongmin.me/posts/ml-stanford/5-nn-training/Explore how neural networks are trained with gradient descent, softmax, and backpropagation using TensorFlow. Understand activation functions and multiclass classification techniques.Thu, 28 Mar 2024 00:00:00 GMTMachine LearningNeural NetworksTensorFlowhttps://jongmin.me/posts/ml-stanford/4-neural-networks/https://jongmin.me/posts/ml-stanford/4-neural-networks/A comprehensive guide to neural networks, forward propagation, TensorFlow implementation, and efficient matrix computations.Tue, 26 Mar 2024 12:00:00 GMTMachine LearningNeural NetworksTensorFlowhttps://jongmin.me/posts/ml-stanford/3-classification/https://jongmin.me/posts/ml-stanford/3-classification/A comprehensive breakdown of logistic regression, sigmoid function, loss functions, and regularization for classification tasks.Sun, 24 Mar 2024 11:00:00 GMTMachine LearningClassificationLogistic Regressionhttps://jongmin.me/posts/ml-stanford/2-regression/https://jongmin.me/posts/ml-stanford/2-regression/Deep dive into multiple linear regression, vectorization, gradient descent, feature scaling, and polynomial regression.Wed, 20 Mar 2024 10:00:00 GMTMachine LearningRegressionGradient Descenthttps://jongmin.me/posts/ml-stanford/1-introduction/https://jongmin.me/posts/ml-stanford/1-introduction/Overview of supervised and unsupervised learning, linear regression, and gradient descentWed, 20 Mar 2024 00:00:00 GMTMachine LearningRegressionGradient Descent