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Document 1
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DocumentLecture1.1
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Overview 7
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1. แนะนำผู้สอนLecture2.1
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2. ภาพรวมคอร์สLecture2.2
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3. History of AILecture2.3
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4. Machine LearningLecture2.4
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5. Supervised LearningLecture2.5
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6. Supervised Learning WorkflowLecture2.6
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7. Data Preparation & Model EvaluationLecture2.7
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12 Algorithms 13
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8. 12 Algorithms – Linear RegressionLecture3.1
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9. 12 Algorithms – Logistic RegressionLecture3.2
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10. 12 Algorithms – Neural NetworkLecture3.3
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11. 12 Algorithms – Deep LearningLecture3.4
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12. 12 Algorithms – Classification TreeLecture3.5
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13. 12 Algorithms – Regression TreeLecture3.6
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14. 12 Algorithms – k Nearest NeighborLecture3.7
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15. 12 Algorithms – Support Vector ClassificationLecture3.8
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16. 12 Algorithms – Support Vector RegressionLecture3.9
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17. 12 Algorithms – Gaussian ProcessLecture3.10
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18. 12 Algorithms – Linear Discriminant AnalysisLecture3.11
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19. 12 Algorithms – Naive BayesLecture3.12
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20. ตอบคำถามนักเรียน1Lecture3.13
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Workshops 8
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21. Code PipelineLecture4.1
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22. Project1 – Concrete StrengthLecture4.2
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23. Project2 – Heart DiseaseLecture4.3
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24. ตอบคำถามนักเรียน2Lecture4.4
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25. ตอบคำถามนักเรียน3Lecture4.5
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26. Project3 – Plant DiseaseLecture4.6
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27. Project4 – Fake NewsLecture4.7
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28. Project5 – Sound ClassificationLecture4.8
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Working with ChatGPT 4
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29. Introduction to ChatGPTLecture5.1
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30. How to Use ChatGPT AssistantLecture5.2
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31. Recommend Prompt for AI & Machine LearningLecture5.3
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32. ConclusionLecture5.4
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