Machine Learning

[ML] 1. Maximum Likelihood(ML) and Maximum A Posteriori(MAP) Estimation

Bayes rule, Maximum…

[DL] 11. RNN 2(Bidirectional, Deep RNN, Long term connection)

Bidrectional RNN, Deep RNN…

[DL] 10. RNN 1

RNN, Forward and Back propagation, teacher forcing

[DL] 9. CNN2 (Structure and Architecture of CNN)

Basic Structure and variance of CNN(VGG, AlexNet…

[DL] 8. CNN 1(Convolutional Neural Network Basics)

Convolution, Correlation, advantages of CNN

[DL] 7. Optimization Techniques on Gradient Descent and Learning Rate

SGD, Momentum, Adaptive Learning…

[DL] 6. Regularizer and Data Augmentation

L1, L2, Early Stopping, and Data Augmentation

[DL] 5. Weight Initialization and Batch Normalization

Basics of the Weight Initialization and Batch…

[DL] 3. Backpropagation

1. Error Backpropagation

[DL] 1. Learning Algorithms and basic terms of DL

1. What is Learning Algorithm?