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DL the Series ครั้งที่ 1 3
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Welcome + AI Overview + Linear RegressionLecture1.1
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Model Creation of Linear RegressionLecture1.2
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Data Preparation + Model Evaluation + Q&ALecture1.3
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DL the Series ครั้งที่ 2 5
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Basic Workshop : Code Pipeline1Lecture2.1
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Basic Workshop : Code Pipeline2Lecture2.2
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Project1 : AI in MarketingLecture2.3
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Project2 – Project5Lecture2.4
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Assumption of Linear RegressionLecture2.5
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DL the Series ครั้งที่ 3 5
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Problem with Linearly DependentLecture3.1
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SolutionLecture3.2
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RegularizationLecture3.3
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Cross Validation & Feature Scaling & Project5Lecture3.4
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Introduction of Logistic RegressionLecture3.5
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DL the Series ครั้งที่ 4 4
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Logistic Regression (2-class) : Data & ModelLecture4.1
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Logistic Regression (2-class) : Calculation Example – ImprovementLecture4.2
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Model Evaluation for ClassificationLecture4.3
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Workshop (2-class)Lecture4.4
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DL the Series ครั้งที่ 5 4
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Logistic Regression (Multi-Class) : IntroductionLecture5.1
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Logistic Regression (Multi-Class) : Data & ModelLecture5.2
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Logistic Regression (Multi-Class) : Prediction, Improvement & WorkshopLecture5.3
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Cross EntropyLecture5.4
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DL the Series ครั้งที่ 6 5
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Neural Network part1Lecture6.1
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Neural Network part2Lecture6.2
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Deep LearningLecture6.3
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ตอบคำถามนักเรียนLecture6.4
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Deep Learning for RegressionLecture6.5
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DL the Series ครั้งที่ 7 5
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Deep Learning for ClassificationLecture7.1
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Basic Workshop – CodepipelineLecture7.2
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AI in Civil Engineering & AI in HealthcareLecture7.3
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AI in Skin CancerLecture7.4
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Deep Learning InterpretationLecture7.5
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DL the Series ครั้งที่ 8 10
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ตอบคำถาม Deep Learning InterpretationLecture8.1
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Improvement – Speed Up with GPULecture8.2
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Improvement – Imbalanced ClassLecture8.3
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Improvement – RegularizationLecture8.4
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Improvement – OptimizerLecture8.5
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Advanced Workshop – House PriceLecture8.6
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Advanced Workshop – Diagnosing Alzheimer’sLecture8.7
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Advanced Workshop – Speech RecognitionLecture8.8
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Conclusion of DL the SeriesLecture8.9
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ตอบคำถาม – การใช้ชีวิตของ อ. ครินLecture8.10
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