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1
Sesi 1 (00:00)
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Perkenalan dan Dasar Machine Learning
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2
Sesi 2 (00:00)
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Algoritma: Linear Regression
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3
Sesi 3 (00:00)
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Algoritma: K-NN
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4
Sesi 4 (00:00)
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Algoritma: K Means Clustering
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5
Sesi 5 (00:00)
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Supervised Machine Learning
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6
Sesi 6 (00:00)
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Supervised Machine Learning
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7
Sesi 7 (00:00)
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Evaluation
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8
Sesi 8 (00:00)
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Unsupervised Machine Learning
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9
Sesi 9 (00:00)
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Basic Neural Network
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10
Sesi 10 (00:00)
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TensorFlow Fundamental
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11
Sesi 11 (00:00)
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Optimization
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12
Sesi 12 (00:00)
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Simple Neural Network with TensorFlow
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13
Sesi 13 (00:00)
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Image Classification Model
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14
Sesi 14 (00:00)
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Text Classification Model
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15
Sesi 15 (00:00)
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Evaluasi
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16
Sesi 16 (00:00)
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Transfer Learning dengan TensorFlow
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17
Sesi 17 (00:00)
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Image Segmentation
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18
Sesi 18 (00:00)
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Deploying TensorFlow Model
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19
Sesi 19 & 20 : Final Project - 1 (00:00)
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Final Project -1
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20
Sesi 21 & 22 : Final Project - 2 (00:00)
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Final Project - 2
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21
Sesi Feedback (00:00)
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Course Feedback
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