[Coursera | DL Specialization | 1 ] Neural Networks and DeepLearning]
1.Lecture Information
Lecture
2023년 6월 19일
2.Week 2 | Neural Networks Basics | Logistic Regression as a Neural Network
Binary Classification Logistic Regression is an alogirthm for Binary Classification An example of a Binary Classification Problem : 어떠한 input ima
2023년 6월 19일
3.Week 2 | Neural Networks Basics | Python and Vectorization
In logistic regression, we need to compute$z=w^Tx + b$ ($w \\in R^{(n_z)}, x \\in R^{(n_z)}$)➡️ 여기서 $w, x$는 $n_x$차원의 vector이다.If we had a non-vectoriz
2023년 6월 21일
4.Week 3 | Shallow Neural Networks | Shallow Neural Network
We'll focus on the case of neural networks with what was called a single hidden layer.Input Layer = Layer 0 : Previously, we were using the vector $X$
2023년 6월 27일
5.Week 4 | Deep Neural Networks | Deep Neural Network
We say that logistic regression is a very "shallow" model.Whereas 5 hidden layers is a much "deeper" model.technically logistic regression is a 1-laye
2023년 7월 9일