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