{"id":22398528,"url":"https://github.com/mengyaohuang/artificial-intelligence-foundation","last_synced_at":"2025-03-26T23:42:22.536Z","repository":{"id":257065013,"uuid":"177469057","full_name":"MengyaoHuang/Artificial-Intelligence-Foundation","owner":"MengyaoHuang","description":"Implement some basic algorithms in AI foundation","archived":false,"fork":false,"pushed_at":"2019-03-29T19:06:24.000Z","size":575,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-02-01T05:24:57.284Z","etag":null,"topics":["algorithms-implemented","artificial-intelligence","python3"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/MengyaoHuang.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-03-24T21:02:56.000Z","updated_at":"2020-02-18T02:34:14.000Z","dependencies_parsed_at":"2024-09-14T17:35:32.538Z","dependency_job_id":"c38e7aca-3d09-4b7a-b21a-1ba4a8bfc8e9","html_url":"https://github.com/MengyaoHuang/Artificial-Intelligence-Foundation","commit_stats":null,"previous_names":["mengyaohuang/artificial-intelligence-foundation"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MengyaoHuang%2FArtificial-Intelligence-Foundation","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MengyaoHuang%2FArtificial-Intelligence-Foundation/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MengyaoHuang%2FArtificial-Intelligence-Foundation/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MengyaoHuang%2FArtificial-Intelligence-Foundation/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MengyaoHuang","download_url":"https://codeload.github.com/MengyaoHuang/Artificial-Intelligence-Foundation/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245755596,"owners_count":20667027,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["algorithms-implemented","artificial-intelligence","python3"],"created_at":"2024-12-05T07:11:15.819Z","updated_at":"2025-03-26T23:42:22.515Z","avatar_url":"https://github.com/MengyaoHuang.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Artificial-Intelligence-Foundation\n\nAn advance introduction to AI emphasizing its theoretical underpinnings.  Topics include search, logic, knowledge representation, reasoning planning, decision making under uncertainty, and machine learning.\n\n## Topics to cover\n- Agents, Rationality, Knowledge, Reasoning\n- Python Coding Review (Also see C++ Review Notes)\n- Problem-solving via Search\n- Uninformed Search\n- Informed Search, Heuristic Functions\n- Local search: Gradient descent (Hill climbing), Simulated Annealing, nondeterminism\n- Games, Alpha-Beta Pruning, Intro to Stochastic Games\n- Constraint Satisfaction Problems (CSPs)\n- Logical agents\n- Propositional logic\n- Resolution-refutation\n- First-order logic (FOL) intro\n- Unification; FOL inference and resolution\n- Classical Planning\n- Resource Scheduling; Overview of Knowledge Representation\n- Review of probability, Bayes Rule\n- Probabilistic Reasoning: Bayesian Inference\n- Bayesian Network examples\n- Markov, Hidden Markov Models (HMMs)\n- Utility, Markov Decision Processes (MDPs)\n- MDPs, Partially-observable MDPs (POMDPs)\n- Game theory intro, Intro to learning\n- Supervised Learning: Decision Trees\n- Intro to Neural Nets, Support Vector Machines (SVMs)\n- Reinforcement Learning Introduction\n\n## Guideline for some projects\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmengyaohuang%2Fartificial-intelligence-foundation","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmengyaohuang%2Fartificial-intelligence-foundation","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmengyaohuang%2Fartificial-intelligence-foundation/lists"}