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คอร์ส Content
Chapter 6.6 Basic deep learning for time series forecasting
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Chapter 6.7 Key Takeaways
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แนะนำ VDO ที่เกี่ยวข้องสำหรับการศึกษาเพิ่มเติมด้วยตนเอง
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Lesson 7 Model Evaluation (4 ชั่วโมง 34 นาที)
Key Objectives
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Chapter 7.1 Why do we need model evaluation?
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Chapter 7.2 Binary Classification – Confusion Matrix
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Chapter 7.3 Binary Classification – Evaluation Metrics
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Chapter 7.5 Binary Classification – Thresholding and Precision-Recall Trade-off
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Chapter 7.9 Key Takeaways
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Lesson 8 Ethical Considerations and Bias in AI (41 นาที)
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Chapter 8.1 Introduction to Risk in AI and How to Mitigate Risk
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Chapter 8.2 Risk, Ethics and Responsible AI
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Chapter 8.3 Best Practices, Tools and Application
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Chapter 8.4 Key Takeaways
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Lesson 9 Advanced Predictive AI (1 ชั่วโมง 53 นาที)
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Chapter 9.1 Image Processing
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Chapter 9.2 Sentiment Analysis Steps #1
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Chapter 9.3 Sentiment Analysis: Library & Model
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Chapter 9.5 Key Takeaways
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Lesson 10 Diffusion Model (48 นาที)
Key Objectives
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Chapter 10.1 What is diffusion model
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Chapter 10.2 Diffusion model
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Chapter 10.3 Diffusion tools
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Chapter 10.4 Demo
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Chapter 10.5 Ethics discussion
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Chapter 10.6 Key Takeaways
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Post Test Module 2
แบบประเมินความพึงพอใจ
แบบประเมินความพึงพอใจ Module 2
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Chapter 7.6 Set up ComfyUI Manager
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Chapter 7.7 Develop custom workflow
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Chapter 7.8 Develop custom node
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Chapter 7.9 Key Takeaways
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Lesson 8 Retrieval-Augmented Generation (RAG) with LangChain (1 ชั่วโมง 27 นาที)
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Chapter 8.1 What is RAG?
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Chapter 8.2 Let’s recap LangChain
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Chapter 8.4 Key Takeaways
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Post Test Module 3
แบบประเมินความพึงพอใจ
แบบประเมินความพึงพอใจ Module 3
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(ภาคการเรียนรู้ผ่านระบบ e-learning) ประจำปี 2568
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(ภาคการเรียนรู้ผ่านระบบ e-learning) ประจำปี 2568
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