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Learning Path

Path A: New to Applied ML

  1. projects/deep-learning-math-foundations-showcase
  2. projects/sota-supervised-learning-showcase
  3. projects/sota-unsupervised-semisup-showcase
  4. projects/causalml-kaggle-showcase

Path B: Deep Learning Foundations

  1. projects/deep-learning-math-foundations-showcase
  2. projects/neural-network-foundations-showcase
  3. projects/pytorch-training-regularization-showcase
  4. projects/sota-supervised-learning-showcase

Path C: Decision Science / Causal Focus

  1. projects/sota-supervised-learning-showcase
  2. projects/causalml-kaggle-showcase
  3. projects/xai-fairness-audit-showcase
  4. projects/mlops-drift-production-showcase

Path D: ML in Production Focus

  1. projects/sota-supervised-learning-showcase
  2. projects/mlops-drift-production-showcase
  3. projects/batch-vs-stream-ml-systems-showcase
  4. projects/model-release-rollout-showcase

Path E: Modeling Optimization Focus

  1. projects/sota-supervised-learning-showcase
  2. projects/automl-hpo-showcase
  3. projects/autoresearch
  4. projects/rl-bandits-policy-showcase
  5. projects/student-support-rl-showcase

Path F: Feature and Representation Focus

  1. projects/sota-supervised-learning-showcase
  2. projects/feature-engineering-dimred-showcase
  3. projects/sota-unsupervised-semisup-showcase

Path G: Short Course (Two Weeks)

  • Day 1-2: deep-learning-math-foundations-showcase
  • Day 3-4: neural-network-foundations-showcase
  • Day 5-6: pytorch-training-regularization-showcase
  • Day 7-8: sota-supervised-learning-showcase
  • Day 9-10: feature-engineering-dimred-showcase
  • Day 11-12: xai-fairness-audit-showcase
  • Day 13-14: mlops-drift-production-showcase

Path M: Deep Learning Mini-Series

  1. projects/deep-learning-math-foundations-showcase
  2. projects/neural-network-foundations-showcase
  3. projects/pytorch-training-regularization-showcase
  4. projects/sota-unsupervised-semisup-showcase

Path H: Contract-First Supervised Workflow

  1. projects/eda-leakage-profiling-showcase
  2. projects/feature-engineering-dimred-showcase
  3. projects/automl-hpo-showcase
  4. projects/xai-fairness-audit-showcase

Path I: Credit Risk Capstone Workflow

  1. projects/eda-leakage-profiling-showcase
  2. projects/feature-engineering-dimred-showcase
  3. projects/credit-risk-classification-capstone-showcase
  4. projects/xai-fairness-audit-showcase

Path J: Ranking and Serving Workflow

  1. projects/learning-to-rank-foundations-showcase
  2. projects/ranking-api-productization-showcase
  3. projects/model-release-rollout-showcase

Path N: NLP Systems Workflow

  1. projects/pytorch-training-regularization-showcase
  2. projects/modern-nlp-pipeline-showcase
  3. projects/learning-to-rank-foundations-showcase
  4. projects/ranking-api-productization-showcase

Path K: Forecasting and Observability Workflow

  1. projects/nyc-demand-forecasting-foundations-showcase
  2. projects/demand-api-observability-showcase
  3. projects/mlops-drift-production-showcase

Path L: Agentic Research Workflow

  1. projects/automl-hpo-showcase
  2. projects/autoresearch
  3. projects/agentic-course-assistant-showcase
  4. projects/adaptive-course-assistant-rl-showcase
  5. projects/model-release-rollout-showcase

Path O: Agent Frameworks Workflow

  1. projects/autoresearch
  2. projects/agentic-course-assistant-showcase
  3. projects/adaptive-course-assistant-rl-showcase
  4. Read projects/adaptive-course-assistant-rl-showcase/artifacts/bridge/learning_agent_story.md after running that project once
  5. projects/modern-nlp-pipeline-showcase
  6. projects/model-release-rollout-showcase

Path P: Reinforcement Learning Decision Workflow

  1. projects/rl-bandits-policy-showcase
  2. projects/student-support-rl-showcase
  3. projects/adaptive-course-assistant-rl-showcase
  4. Re-run projects/adaptive-course-assistant-rl-showcase with make sync-drl && make run-drl-optional to study the DQN/PPO bridge around an agentic tutoring workflow
  5. Re-run projects/student-support-rl-showcase with make sync-drl && make run-drl-optional to compare that broader RL ladder against the more focused agentic-tutoring bridge
  6. projects/model-release-rollout-showcase

Path Q: Learning-Agent Bridge Workflow

  1. projects/agentic-course-assistant-showcase
  2. projects/adaptive-course-assistant-rl-showcase
  3. projects/learning-agents-showcase
  4. Re-run projects/adaptive-course-assistant-rl-showcase with make sync-drl && make run-drl-optional
  5. If you have not already run it, run projects/student-support-rl-showcase; otherwise re-run it with make sync-drl && make run-drl-optional

This path is the cleanest answer to: "how do agent frameworks and learned intervention policies fit together without overclaiming?"

projects/learning-agents-showcase is the standalone capstone in that bridge. Its deterministic core path is runnable today, and the OpenAI Agents SDK bridge, RLHF/DPO/GRPO/RLVR, MARL, and an optional NumPy DQN/PPO deep-RL lane now ship as well.

How To Know You Are Progressing

  • You can explain outputs in plain language.
  • You can justify model choices with evidence.
  • You can describe one limitation or risk per method.
  • You can propose a production or governance guardrail for each modeling workflow.

Coverage Cross-Reference

Use docs/aspect-coverage-matrix.md to confirm which project demonstrates each method (splits, imbalance handling, explainability, HPO, tracking, and productionization).

Track Pages

For track-level documentation with artifact-focused guidance:

  • docs/tracks/foundations.md
  • docs/tracks/production.md
  • docs/tracks/ranking.md
  • docs/tracks/forecasting.md
  • docs/tracks/responsible-ai.md
  • docs/tracks/optimization.md
  • docs/tracks/reinforcement-learning.md
  • docs/tracks/agent-frameworks.md
  • docs/tracks/agentic-rl.md