Answers.Body: <p>AI is an extremely broad area intersecting areas such as algorithm computability and complexity analysis of computer science, neural networks of cognitive science, statistical inference and machine learning, agent (sequential) decision theory and ethics, knowledge representation and ontology engineering, multi-agent cooperative/non-cooperative game theory, language modeling and NLP, computer vision and robotics.</p>
  <p>With 28 chapters in total, Russell's <em>Artificial Intelligence - A Modern Approach</em> (4th edition) is a classic reference gathering most useful and practical resources and guidance covering all above mentioned topics of AI comprehensively, which could be a start place for you to delve into AI.</p>
  
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Answers.CreationDate: 2024-12-11T09:20:39.383Z
Answers.Text: it looks good though it feels very heavy theory
Answers.UserDisplayName: Ash_Blanc
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Answers.CreationDate: 2024-12-11T09:32:11.790Z
Answers.Text: any similar but shorter alternatives ?
Answers.UserDisplayName: Ash_Blanc
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-12-11T22:13:47.173Z
Answers.Text: My answer specifically addresses your broad AI scope with practical and useful coverage, and real AI does inherently carry heavy theory otherwise it'll be easy like general programming. Russell's book seems heavy but actually is introductory level for each major topic, except some chapter or section are more niche and you can skip on first read such as CSP or some search algos with no harm. Once you get a rough idea of all AI related topics, you can delve into separate topic via other references which is another question for another day, you can also post questions here during your reading.
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Answers.CreationDate: 2024-12-11T03:31:18.017Z
Answers.LastActivityDate: 2024-12-11T03:31:18.017Z
Answers.UserDisplayName: cinch
Body: <p>As the field is evolving at such a pace , the topics/concepts which are about to learn today just gets replaced with something better/newer alternative tomorrow and its such mess of resources (which often leads to distractions). So I thought if we could gather the most useful/practical &amp; good resources/guides covering the major ai topics (here as answers) ?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-12-11T10:49:03.573Z
Comments.Text: This is too broad. Ask a more specific question, but before that check out our questions that ask for resources on specific topics. We already have some like, https://ai.stackexchange.com/q/20355/2444, https://ai.stackexchange.com/q/3647/2444, or https://ai.stackexchange.com/q/20910/2444, which I gave an answer to.
Comments.UserDisplayName: nbro
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Comments.CreationDate: 2024-12-11T15:59:59.753Z
Comments.Text: @nbro most of them are quite old
Comments.UserDisplayName: Ash_Blanc
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-12-11T16:01:40.213Z
Comments.Text: You can ask a new similar specific question and explain why the answers to an existing question do not satisfy you. But this post is currently too broad.
Comments.UserDisplayName: nbro
Tags: <machine-learning><deep-learning><agi>
Title: gathering precise practical guides/resources/links on ai topics in one place
UserDisplayName: Ash_Blanc
ThreadText: # gathering precise practical guides/resources/links on ai topics in one place
  
  (Asked by: username_0 on 2024-12-10)
  
  As the field is evolving at such a pace , the topics/concepts which are about to learn today just gets replaced with something better/newer alternative tomorrow and its such mess of resources (which often leads to distractions). So I thought if we could gather the most useful/practical & good resources/guides covering the major ai topics (here as answers) ?
  
  **Tags:** machine-learning, deep-learning, agi
  > **Comments:**
  > **username_1**: This is too broad. Ask a more specific question, but before that check out our questions that ask for resources on specific topics. We already have some like, https://ai.stackexchange.com/q/20355/2444, https://ai.stackexchange.com/q/3647/2444, or https://ai.stackexchange.com/q/20910/2444, which I gave an answer to.  
  > **username_0**: @nbro most of them are quite old  
  > **username_1**: You can ask a new similar specific question and explain why the answers to an existing question do not satisfy you. But this post is currently too broad.  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2024-12-11. Score: 0
  
  AI is an extremely broad area intersecting areas such as algorithm computability and complexity analysis of computer science, neural networks of cognitive science, statistical inference and machine learning, agent (sequential) decision theory and ethics, knowledge representation and ontology engineering, multi-agent cooperative/non-cooperative game theory, language modeling and NLP, computer vision and robotics.
  
  With 28 chapters in total, Russell's *Artificial Intelligence - A Modern Approach* (4th edition) is a classic reference gathering most useful and practical resources and guidance covering all above mentioned topics of AI comprehensively, which could be a start place for you to delve into AI.
  
  > **Comments:**
  > **username_0**: it looks good though it feels very heavy theory  
  > **username_0**: any similar but shorter alternatives ?  
  > **username_2**: My answer specifically addresses your broad AI scope with practical and useful coverage, and real AI does inherently carry heavy theory otherwise it'll be easy like general programming. Russell's book seems heavy but actually is introductory level for each major topic, except some chapter or section are more niche and you can skip on first read such as CSP or some search algos with no harm. Once you get a rough idea of all AI related topics, you can delve into separate topic via other references which is another question for another day, you can also post questions here during your reading.  
  
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