enggen · Captainspockears · Sep 1, 2020 · Sep 1, 2020 · Sep 1, 2020
diff --git a/Convolutional Neural Networks/Notes/41.pdf b/Convolutional Neural Networks/Notes/41.pdf
diff --git a/Convolutional Neural Networks/Notes/42.pdf b/Convolutional Neural Networks/Notes/42.pdf
diff --git a/Convolutional Neural Networks/Notes/43.pdf b/Convolutional Neural Networks/Notes/43.pdf
diff --git a/Convolutional Neural Networks/Notes/44.pdf b/Convolutional Neural Networks/Notes/44.pdf
diff --git a/... Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/Notes/21.pdf b/... Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/Notes/21.pdf
diff --git a/... Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/Notes/22.pdf b/... Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/Notes/22.pdf
diff --git a/... Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/Notes/23.pdf b/... Deep Neural Networks Hyperparameter tuning, Regularization and Optimization/Notes/23.pdf
diff --git a/Neural Networks and Deep Learning/Notes/11.pdf b/Neural Networks and Deep Learning/Notes/11.pdf
diff --git a/Neural Networks and Deep Learning/Notes/12.pdf b/Neural Networks and Deep Learning/Notes/12.pdf
diff --git a/Neural Networks and Deep Learning/Notes/13.pdf b/Neural Networks and Deep Learning/Notes/13.pdf
diff --git a/Neural Networks and Deep Learning/Notes/14.pdf b/Neural Networks and Deep Learning/Notes/14.pdf
diff --git a/README.md b/README.md
@@ -1,50 +1,52 @@
 # Deep Learning Specialization on Coursera
 ### [Master Deep Learning, and Break into AI](https://www.coursera.org/specializations/deep-learning)
 
-This is my personal projects for the course. The course covers deep learning from begginer level to advanced. Highly recommend anyone wanting to break into AI. 
+This is my personal project for the course. The course covers deep learning from beginner level to advanced. I highly recommend it to anyone wanting to break into AI. Also note that this is strictly for future reference of the algorithms only and plagerism of the answers violates the policies of Coursera.
+
+I would like to thank [captainspockears](https://github.com/Captainspockears) for providing the notes for this course and making necessary changes.
 
 Instructor: [Andrew Ng, DeepLearning.ai]()
 
  ## Course 1. [Neural Networks and Deep Learning](https://www.youtube.com/watch?v=CS4cs9xVecg&list=PLkDaE6sCZn6Ec-XTbcX1uRg2_u4xOEky0)
 
-1. Week1 - [Introduction to deep learning](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Neural%20Networks%20and%20Deep%20Learning)
-2. Week2 - [Neural Networks Basics](https://github.com/enggen/Deep-Learning-deeplearning.ai/blob/master/Neural%20Networks%20and%20Deep%20Learning/Logistic%20Regression%20with%20a%20Neural%20Network%20mindset.ipynb)
-3. Week3 - [Shallow neural networks](https://github.com/enggen/Deep-Learning-deeplearning.ai/blob/master/Neural%20Networks%20and%20Deep%20Learning/Logistic%20Regression%20with%20a%20Neural%20Network%20mindset.ipynb)
-4. Week4 - [Deep Neural Networks](https://github.com/enggen/Deep-Learning-deeplearning.ai/tree/master/Neural%20Networks%20and%20Deep%20Learning)
+1. Week1 - [Introduction to deep learning](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Neural%20Networks%20and%20Deep%20Learning) | [Notes](Neural%20Networks%20and%20Deep%20Learning/Notes/11.pdf)
+2. Week2 - [Neural Networks Basics](https://github.com/enggen/Deep-Learning-deeplearning.ai/blob/master/Neural%20Networks%20and%20Deep%20Learning/Logistic%20Regression%20with%20a%20Neural%20Network%20mindset.ipynb) | [Notes](Neural%20Networks%20and%20Deep%20Learning/Notes/12.pdf)
+3. Week3 - [Shallow neural networks](https://github.com/enggen/Deep-Learning-deeplearning.ai/blob/master/Neural%20Networks%20and%20Deep%20Learning/Logistic%20Regression%20with%20a%20Neural%20Network%20mindset.ipynb) | [Notes](Neural%20Networks%20and%20Deep%20Learning/Notes/13.pdf)
+4. Week4 - [Deep Neural Networks](https://github.com/enggen/Deep-Learning-deeplearning.ai/tree/master/Neural%20Networks%20and%20Deep%20Learning) | [Notes](Neural%20Networks%20and%20Deep%20Learning/Notes/14.pdf)
 
 ## Course 2. [Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization](https://www.youtube.com/watch?v=1waHlpKiNyY&list=PLkDaE6sCZn6Hn0vK8co82zjQtt3T2Nkqc)
 
 1. Week1 - [Practical aspects of Deep Learning](https://github.com/enggen/Deep-Learning-deeplearning.ai/tree/master/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
-2. Week2 - [Optimization algorithms](https://github.com/enggen/Deep-Learning-deeplearning.ai/tree/master/Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization)
-3. Week3 - [Hyperparameter tuning, Batch Normalization and Programming Frameworks](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization)
+         - Setting up your optimization problem  | [Notes](Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Notes/21.pdf)
+2. Week2 - [Optimization algorithms](https://github.com/enggen/Deep-Learning-deeplearning.ai/tree/master/Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization) | [Notes](Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Notes/22.pdf)
+3. Week3 - [Hyperparameter tuning, Batch Normalization and Programming Frameworks](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization) | [Notes](Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Notes/23.pdf)
 
 ## Course 3. [Structuring Machine Learning Projects](https://www.youtube.com/watch?v=dFX8k1kXhOw&list=PLkDaE6sCZn6E7jZ9sN_xHwSHOdjUxUW_b)
 
 1. Week1 - [Introduction to ML Strategy](https://github.com/enggen/Deep-Learning-Coursera/blob/master/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
+         - Comparing to human-level performance | [Notes](Structuring%20Machine%20Learning%20Projects/Notes/31.pdf)
 2. Week2 - [ML Strategy (2)](https://github.com/enggen/Deep-Learning-Coursera/blob/master/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
+         - End-to-end deep learning | [Notes](Structuring%20Machine%20Learning%20Projects/Notes/32.pdf)
 
  ## Course 4. [Convolutional Neural Networks](https://www.youtube.com/watch?v=ArPaAX_PhIs&list=PLkDaE6sCZn6Gl29AoE31iwdVwSG-KnDzF)
 
- 1. Week1 - [Foundations of Convolutional Neural Networks](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Convolutional%20Neural%20Networks/Week1)
+ 1. Week1 - [Foundations of Convolutional Neural Networks](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Convolutional%20Neural%20Networks/Week1) | [Notes](Convolutional%20Neural%20Networks/Notes/41.pdf)
  2. Week2 - [Deep convolutional models: case studies](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Convolutional%20Neural%20Networks/Week2/ResNets) - 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)
+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) | [Notes](Convolutional%20Neural%20Networks/Notes/42.pdf)
  3. [Week3 - Object detection](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Convolutional%20Neural%20Networks/Week3/Car%20detection%20for%20Autonomous%20Driving) - 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)
- 4. Week4 - [Special applications: Face recognition & Neural style transfer](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Convolutional%20Neural%20Networks/Week4) - Papers for read: [DeepFace](https://www.cs.toronto.edu/~ranzato/publications/taigman_cvpr14.pdf), [FaceNet](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Schroff_FaceNet_A_Unified_2015_CVPR_paper.pdf)
+Unified, Real-Time Object Detection](https://arxiv.org/pdf/1506.02640.pdf), [YOLO](https://arxiv.org/pdf/1612.08242.pdf) | [Notes](Convolutional%20Neural%20Networks/Notes/43.pdf)
+ 4. Week4 - [Special applications: Face recognition & Neural style transfer](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Convolutional%20Neural%20Networks/Week4) - Papers for read: [DeepFace](https://www.cs.toronto.edu/~ranzato/publications/taigman_cvpr14.pdf), [FaceNet](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Schroff_FaceNet_A_Unified_2015_CVPR_paper.pdf) | [Notes](Convolutional%20Neural%20Networks/Notes/44.pdf)
 
  ## Course 5. [Sequence Models](https://www.youtube.com/watch?v=DejHQYAGb7Q&list=PLkDaE6sCZn6F6wUI9tvS_Gw1vaFAx6rd6)
- 1. Week1 - [Recurrent Neural Networks](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Sequence%20Models/Week1)
- 2. Week2 - [Natural Language Processing & Word Embeddings](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Sequence%20Models/Week2)
- 3. Week3 - [Sequence models & Attention mechanism](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Sequence%20Models/Week3)
+ 1. Week1 - [Recurrent Neural Networks](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Sequence%20Models/Week1) | [Notes](Sequence%20Models/Notes/51.pdf)
+ 2. Week2 - [Natural Language Processing & Word Embeddings](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Sequence%20Models/Week2) | [Notes](Sequence%20Models/Notes/52.pdf)
+ 3. Week3 - [Sequence models & Attention mechanism](https://github.com/enggen/Deep-Learning-Coursera/tree/master/Sequence%20Models/Week3) | [Notes](Sequence%20Models/Notes/53.pdf)
 
 <p align="center"> *************************************************************************************************************************************</p>
 
diff --git a/Sequence Models/Notes/51.pdf b/Sequence Models/Notes/51.pdf
diff --git a/Sequence Models/Notes/52.pdf b/Sequence Models/Notes/52.pdf
diff --git a/Sequence Models/Notes/53.pdf b/Sequence Models/Notes/53.pdf
diff --git a/Structuring Machine Learning Projects/Notes/31.pdf b/Structuring Machine Learning Projects/Notes/31.pdf
diff --git a/Structuring Machine Learning Projects/Notes/32.pdf b/Structuring Machine Learning Projects/Notes/32.pdf