# Andrew NG Notes Collection

**This is the first course of the deep learning specialization at [Coursera](https://www.coursera.org/specializations/deep-learning) which is moderated by [DeepLearning.ai](http://deeplearning.ai/). The course is taught by Andrew Ng.**

**<Span style="color:red;">Andrew NG Machine Learning Notebooks  :</span>**  [**Reading**](https://github.com/ashishpatel26/Andrew-NG-Notes/tree/master/Machine%20Learning%20notebooks%20By%20Andrew%20NG)   

**<Span style="color:red;">Deep learning Specialization Notes in One pdf :</span>**  [**Reading**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20learning%20by%20AndrewNG%20Tutorial%20%20Notes.pdf)

| **Sr No** | **Article Reading**                                          |
| --------- | :----------------------------------------------------------- |
| **1.**    | **[Neural Network Deep Learning](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-1-neural-network-deep-learning.md)** |
| **2.**    | **[Improving Deep learning Network](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-2-improving-deep-learning-network.md)** |
| **3.**    | **[Structure of ML Projects](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-3-structuring-ml-projects.md)** |
| **4.**    | **[Convolutions Neural Network](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-4-convolutional-neural-network.md)** |
| **5.**    | **[Sequence Models](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-5-sequence-models.md)** |

| Sr. No | MOOC LECTURE LINK                                            |
| ------ | ------------------------------------------------------------ |
| 1.     | [**Machine learning by Andrew-NG**](https://www.youtube.com/playlist?list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN) |
|        | **DEEP LEARNING SERIES**                                     |
| 1.     | [**Neural Network and Deep Learning**](https://www.youtube.com/playlist?list=PLkDaE6sCZn6Ec-XTbcX1uRg2_u4xOEky0) |
| 2.     | [**Improving deep neural networks: hyperparameter tuning, regularization and optimization**](https://www.youtube.com/playlist?list=PLkDaE6sCZn6Hn0vK8co82zjQtt3T2Nkqc) |
| 3.     | [**Structuring Machine Learning Projects**](https://www.youtube.com/playlist?list=PLkDaE6sCZn6E7jZ9sN_xHwSHOdjUxUW_b) |
| 4.     | [**Convolution Neural Network**](https://www.youtube.com/playlist?list=PLkDaE6sCZn6Gl29AoE31iwdVwSG-KnDzF) |
| 5.     | [**Sequence Models**](https://www.youtube.com/playlist?list=PLkDaE6sCZn6F6wUI9tvS_Gw1vaFAx6rd6) |
| 6.     | [**CS230: Deep Learning \| Autumn 2018**](https://www.youtube.com/playlist?list=PLoROMvodv4rOABXSygHTsbvUz4G_YQhOb ) |

## [**1.Neural Network Deep Learning**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-1-neural-network-deep-learning.md)   

## ![](https://systweak1.vo.llnwd.net/content/wp/systweakblogsnew/uploads_new/2018/03/hidden-layers-in-network.gif)

* **This Notes Give you brief introduction about :** 
  * [**What is neural network? How it's work?**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-1-neural-network-deep-learning.md#what-is-a-neural-network-nn)
  * [**Supervised Learning using Neural Network**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-1-neural-network-deep-learning.md#neural-networks-basics)
  * [**Shallow Neural Network Design**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-1-neural-network-deep-learning.md#shallow-neural-networks)
  * [**Deep Neural Network**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-1-neural-network-deep-learning.md#deep-neural-networks)
*  **Notebooks** :
  * Week1 - [**Introduction to deep learning**](https://github.com/ashishpatel26/Andrew-NG-Notes/tree/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Convolutional%20Neural%20Networks/Week1)
  * Week2 - [**Neural Networks Basics**](https://nbviewer.jupyter.org/github/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Neural%20Networks%20and%20Deep%20Learning/Logistic%20Regression%20with%20a%20Neural%20Network%20mindset.ipynb)
  * Week3 - [**Shallow neural networks**](https://nbviewer.jupyter.org/github/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Neural%20Networks%20and%20Deep%20Learning/Logistic%20Regression%20with%20a%20Neural%20Network%20mindset.ipynb)
  * Week4 - [**Deep Neural Networks**](https://nbviewer.jupyter.org/github/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Neural%20Networks%20and%20Deep%20Learning/Building%20your%20Deep%20Neural%20Network%20-%20Step%20by%20Step.ipynb) 

## [**2 Improving Deep learning Network**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-2-improving-deep-learning-network.md)

## ![](https://i.pinimg.com/originals/63/62/8f/63628f546ad55fd31091e23c623cb9f5.gif)



* **This Notes Give you introduction about :** 
  * [**Practical aspects of Deep Learning**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-2-improving-deep-learning-network.md#practical-aspects-of-deep-learning)
  * [**Optimization algorithms**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-2-improving-deep-learning-network.md#optimization-algorithms)
  * [**Hyperparameter tuning, Batch Normalization and Programming Frameworks**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-2-improving-deep-learning-network.md#hyperparameter-tuning-batch-normalization-and-programming-frameworks)
* **Notebooks**:
  * Week1 - [**Practical aspects of Deep Learning**](https://github.com/ashishpatel26/Andrew-NG-Notes/tree/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization)
       - Setting up your Machine Learning Application
    - Regularizing your neural network
    - Setting up your optimization problem
  * Week2 - [**Optimization algorithms**](https://nbviewer.jupyter.org/github/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Optimization%20methods.ipynb)
  * Week3 - [**Hyperparameter tuning, Batch Normalization and Programming Frameworks**](https://github.com/ashishpatel26/Andrew-NG-Notes/tree/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization)

## [**3.Structure ML Projects**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-3-structuring-ml-projects.md)

![](https://i.pinimg.com/originals/9b/fa/97/9bfa978a4cf40fe2cdf8c710deb9b6f9.png)



* **In This Notes, you can learn about How to Structure Machine Learning Project:**
  * [**Why ML Structure?**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-3-structuring-ml-projects.md#ml-strategy-1)
  * [**Error Analysis**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-3-structuring-ml-projects.md#ml-strategy-2)
* **Notebooks:**
  * Week1 - [**Introduction to ML Strategy**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Structuring%20Machine%20Learning%20Projects/Week%201%20Quiz%20-%20Bird%20recognition%20in%20the%20city%20of%20Peacetopia%20(case%20study).md)
       - Setting up your goal
    - Comparing to human-level performance
  * Week2 - [**ML Strategy (2)**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Structuring%20Machine%20Learning%20Projects/Week%202%20Quiz%20-%20Autonomous%20driving%20(case%20study).md)
       - Error Analysis
    - Mismatched training and dev/test set
    - Learning from multiple tasks
    - End-to-end deep learning

## [**4.Convolution Neural Network**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-4-convolutional-neural-network.md)

* **Matrix Multiplication Between Image and Kernel Known as *Convolution Operation***

![](https://i.stack.imgur.com/9OZKF.gif)



![](https://cdn-images-1.medium.com/max/600/1*GdxHFaUDbvTXJreKg3S8SQ.gif)







![](https://www.guru99.com/images/tensorflow/082918_1325_ConvNetConv9.gif)



* **In This Notes, you can learn about Brief architecture CNN:**
  * [**Foundations of CNNs**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-4-convolutional-neural-network.md#foundations-of-cnns)
  * [**Deep convolutional models: case studies**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-4-convolutional-neural-network.md#deep-convolutional-models-case-studies)
  * [**Object detection**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-4-convolutional-neural-network.md#object-detection)
  * [**Special applications: Face recognition & Neural style transfer**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-4-convolutional-neural-network.md#special-applications-face-recognition--neural-style-transfer)
*  **Notebooks :** 
  * Week1 - [**Foundations of Convolutional Neural Networks**](https://nbviewer.jupyter.org/github/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Convolutional%20Neural%20Networks/Week1/Convolution%20model%20-%20Step%20by%20Step.ipynb)
  * Week2 - [**Deep convolutional models: case studies**](https://nbviewer.jupyter.org/github/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Convolutional%20Neural%20Networks/Week2/ResNets/Residual%20Networks.ipynb) 
    - **Papers for read:**  
      - [**ImageNet Classification with Deep Convolutional Neural Networks**](https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf)
      - [**Very Deep Convolutional Networks For Large-Scale Image Recognition**](https://arxiv.org/pdf/1409.1556.pdf)
  * Week3 - [**Object detection**](https://nbviewer.jupyter.org/github/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Convolutional%20Neural%20Networks/Week3/Car%20detection%20for%20Autonomous%20Driving/Autonomous%20driving%20application%20-%20Car%20detection.ipynb) 
    - **Papers for read:** 
      - [**You Only Look Once: Unified, Real-Time Object Detection**](https://arxiv.org/pdf/1506.02640.pdf)
      - [**YOLO**](https://arxiv.org/pdf/1612.08242.pdf)
  * Week4 - [**Special applications: Face recognition & Neural style transfer**](https://github.com/ashishpatel26/Andrew-NG-Notes/tree/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Convolutional%20Neural%20Networks/Week4) 
    - **Papers for read:** 
      - [**DeepFace**](https://www.cs.toronto.edu/~ranzato/publications/taigman_cvpr14.pdf) ([**Notebook**](https://nbviewer.jupyter.org/github/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Convolutional%20Neural%20Networks/Week4/Face%20Recognition/Face%20Recognition%20for%20the%20Happy%20House.ipynb))
      - [**FaceNet**](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Schroff_FaceNet_A_Unified_2015_CVPR_paper.pdf)
      - [**Neural Style Transfer**](https://nbviewer.jupyter.org/github/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Convolutional%20Neural%20Networks/Week4/Neural%20Style%20Transfer/Art%20Generation%20with%20Neural%20Style%20Transfer.ipynb)

## [**5.Sequence Models**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-5-sequence-models.md)

![](https://3.bp.blogspot.com/-3Pbj_dvt0Vo/V-qe-Nl6P5I/AAAAAAAABQc/z0_6WtVWtvARtMk0i9_AtLeyyGyV6AI4wCLcB/s1600/nmt-model-fast.gif)

---

* **Vanila RNN**

  ![](https://cdn-images-1.medium.com/max/880/1*xn5kA92_J5KLaKcP7BMRLA.gif)

* **LSTM**

![](https://cdn-images-1.medium.com/max/880/1*goJVQs-p9kgLODFNyhl9zA.gif)

* **GRU**

![](https://cdn-images-1.medium.com/max/880/1*FpRS0C3EHQnELVaWRvb8bg.gif)

* **In This Section, you can learn about Sequence to Sequence Learning**

  * [**Recurrent Neural Networks**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-5-sequence-models.md#recurrent-neural-networks)
  * [**Natural Language Processing & Word Embeddings**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-5-sequence-models.md#natural-language-processing--word-embeddings)
  * [**Sequence models & Attention mechanism**](https://github.com/ashishpatel26/Andrew-NG-Notes/blob/master/andrewng-p-5-sequence-models.md#sequence-models--attention-mechanism)

* **Notebooks:**

  * Week1 - [**Recurrent Neural Networks**](https://nbviewer.jupyter.org/github/ashishpatel26/Andrew-NG-Notes/blob/master/Deep%20Learning%20Notebooks%20by%20Andrew%20NG/Sequence%20Models/Week1/Building%20a%20Recurrent%20Neural%20Network%20-%20Step%20by%20Step/Building%20a%20Recurrent%20Neural%20Network%20-%20Step%20by%20Step.ipynb)
  * Week2 - [**Natural Language Processing & Word Embeddings**](https://github.com/ashishpatel26/Deep-Learning-Coursera/tree/master/Sequence%20Models/Week2)
  * Week3 - [**Sequence models & Attention mechanism**](https://github.com/ashishpatel26/Deep-Learning-Coursera/tree/master/Sequence%20Models/Week3)

  

**Thanks for Reading....Happy Learning...!!!**