---
# System prepended metadata

title: Homework 2
tags: [homework, NTHU]

---

# Homework 2

> National Tsing Hua University
> Fall 2022 11110IPT 5530
> Deep Learning in Biomedical Optical Imaging

###### tags: `homework` `NTHU`

:::info
- **Deadline:** ⚠️2022.10.04 00:00
- **Name:** Akshay Walkoli 
- **Student ID:** 110066421
:::

[ToC]

## 1. Planar data classification with one hidden layer

### Exercise 1
![](https://i.imgur.com/dVW4n2B.jpg)

### Exercise 2 - layer_sizes
![](https://i.imgur.com/NyFWxmz.jpg)
![](https://i.imgur.com/8eCJVfQ.jpg)

 

### Exercise 3 - initialize_parameters
![](https://i.imgur.com/Cu0hqRb.jpg)
![](https://i.imgur.com/5gh4OCw.jpg)
![](https://i.imgur.com/uoCEo7h.jpg)



### Exercise 4 - forward_propagation
![](https://i.imgur.com/pYepiMP.jpg)
![](https://i.imgur.com/EdIWcID.jpg)
![](https://i.imgur.com/zMpuKkz.jpg)


### Exercise 5 - compute_cost
![](https://i.imgur.com/aX0d66s.jpg)
![](https://i.imgur.com/55dBQ2n.jpg)


### Exercise 6 - backward_propagation
![](https://i.imgur.com/vYoGCrY.jpg)
![](https://i.imgur.com/iXYHgIY.jpg)
![](https://i.imgur.com/8scMVLq.jpg)
![](https://i.imgur.com/CK194rY.jpg)

### Exercise 7 - update_parameters
![](https://i.imgur.com/vnQF85y.jpg)
![](https://i.imgur.com/QD0ODpa.jpg)
![](https://i.imgur.com/9O6KAaD.jpg)
![](https://i.imgur.com/dqWyjDY.jpg)

### Exercise 8 - nn_model
![](https://i.imgur.com/GlKJIWt.jpg)
![](https://i.imgur.com/NndiKrK.jpg)
![](https://i.imgur.com/2xb2TSp.jpg)
![](https://i.imgur.com/hATEQbN.jpg)


### Exercise 9 - predict
![](https://i.imgur.com/UYPZ6dU.jpg)
![](https://i.imgur.com/l9Z2sMG.jpg)
![](https://i.imgur.com/xvMOwLd.jpg)
![](https://i.imgur.com/8hPXaGx.jpg)
![](https://i.imgur.com/xksTAAO.jpg)


---

## 2. Building your Deep Neural Network

### Exercise 1 - initialize_parameters
![](https://i.imgur.com/seuYGoF.jpg)
![](https://i.imgur.com/v9Y7q1f.jpg)


### Exercise 2 - initialize_parameters_deep
![](https://i.imgur.com/2BFH5Bd.jpg)
![](https://i.imgur.com/8HzL5yv.jpg)

### Exercise 3 - linear_forward
![](https://i.imgur.com/A8mJNHw.jpg)
![](https://i.imgur.com/Cqm1eA7.jpg)


### Exercise 4 - linear_activation_forward
![](https://i.imgur.com/Qp76PpP.jpg)
![](https://i.imgur.com/vdze6dl.jpg)


### Exercise 5 - L_model_forward
![](https://i.imgur.com/8jeBP8m.jpg)
![](https://i.imgur.com/pcrCVc6.jpg)



### Exercise 6 - compute_cost
![](https://i.imgur.com/JtR6Eqq.jpg)
![](https://i.imgur.com/MCcRtnt.jpg)


### Exercise 7 - Linear Backwards
![](https://i.imgur.com/ZvDVxiW.jpg)
![](https://i.imgur.com/wNFAQS5.jpg)


### Exercise 8 - linear_activation_backwards
![](https://i.imgur.com/S4drdZX.jpg)
![](https://i.imgur.com/bX4A4g1.jpg)
![](https://i.imgur.com/FAnkEBV.jpg)



### Exercise 9 - L_model_backwards
![](https://i.imgur.com/4n8L5Dw.jpg)
![](https://i.imgur.com/JlXRERn.jpg)
![](https://i.imgur.com/tAuPf9i.jpg)
![](https://i.imgur.com/VnFdp4u.jpg)



### Exercise 10 - update parameters
![](https://i.imgur.com/NHmpSyZ.jpg)
![](https://i.imgur.com/jAKliIj.jpg)





