文件列表:

C1 - Neural Networks and Deep Learning (0, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes (0, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images (0, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\02.png (70931, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\03.png (146536, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\04.png (152504, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\05.png (251072, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\06.png (234513, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\07.png (196499, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\08.png (185297, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\09.png (3296, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\10.png (10633, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\11.png (197873, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\Others (0, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\Others\01.jpg (27048, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\Others\02.png (100587, 2022-02-07)
C1 - Neural Networks and Deep Learning\Notes\Images\Others\03.png (6187, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 1 (0, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 1\Week 1 Quiz - Introduction to deep learning.md (4030, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 1\Week 1 Quiz - Introduction to deep learning.pdf (1098310, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2 (0, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network (0, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\Logistic_Regression_with_a_Neural_Network_mindset_v6a.ipynb (147824, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\datasets (0, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\datasets\test_catvnoncat.h5 (131, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\datasets\train_catvnoncat.h5 (132, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\images (0, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\images\LogReg_kiank.png (191592, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\images\cat_in_iran.jpg (601084, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\images\gargouille.jpg (310181, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\images\image1.png (265708, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\images\image2.png (154439, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\images\la_defense.jpg (339673, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\images\my_image.jpg (636273, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\images\my_image2.jpg (94439, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Logistic Regression as a Neural Network\lr_utils.py (882, 2022-02-07)
C1 - Neural Networks and Deep Learning\Week 2\Python Basics with Numpy (0, 2022-02-07)
... ...

# Deep Learning Specialization on Coursera (offered by deeplearning.ai) Programming assignments and quizzes from all courses in the Coursera [Deep Learning specialization](https://www.coursera.org/specializations/deep-learning) offered by `deeplearning.ai`. Instructor: [Andrew Ng](http://www.andrewng.org/) ## Notes ### For detailed interview-ready notes on all courses in the Coursera Deep Learning specialization, refer [www.aman.ai](https://aman.ai/). ## Setup Run ```setup.sh``` to (i) download a pre-trained VGG-19 dataset and (ii) extract the zip'd pre-trained models and datasets that are needed for all the assignments. ## Credits This repo contains my work for this specialization. The code base, quiz questions and diagrams are taken from the [Deep Learning Specialization on Coursera](https://www.coursera.org/specializations/deep-learning), unless specified otherwise. ## 2021 Version This specialization was updated in April 2021 to include developments in deep learning and programming frameworks, with the biggest change being shifting from TensorFlow 1 to TensorFlow 2. This repo has been updated accordingly as well. ## Programming Assignments ### Course 1: Neural Networks and Deep Learning - [Week 2 - PA 1 - Python Basics with Numpy](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%202/Python%20Basics%20with%20Numpy/Python_Basics_With_Numpy_v3a.ipynb) - [Week 2 - PA 2 - Logistic Regression with a Neural Network mindset](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%202/Logistic%20Regression%20as%20a%20Neural%20Network/Logistic_Regression_with_a_Neural_Network_mindset_v6a.ipynb) - [Week 3 - PA 3 - Planar data classification with one hidden layer](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%203/Planar%20data%20classification%20with%20one%20hidden%20layer/Planar_data_classification_with_onehidden_layer_v6c.ipynb) - [Week 4 - PA 4 - Building your Deep Neural Network: Step by Step](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%204/Building%20your%20Deep%20Neural%20Network%20-%20Step%20by%20Step/Building_your_Deep_Neural_Network_Step_by_Step_v8a.ipynb) - [Week 4 - PA 5 - Deep Neural Network for Image Classification: Application](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%204/Deep%20Neural%20Network%20Application_%20Image%20Classification/Deep%20Neural%20Network%20-%20Application%20v8.ipynb) ### Course 2: Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization - [Week 1 - PA 1 - Initialization](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C2%20-%20Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%201/Initialization/Initialization.ipynb) - [Week 1 - PA 2 - Regularization](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C2%20-%20Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%201/Regularization/Regularization_v2a.ipynb) - [Week 1 - PA 3 - Gradient Checking](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C2%20-%20Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%201/Gradient%20Checking/Gradient%20Checking%20v1.ipynb) - [Week 2 - PA 4 - Optimization Methods](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C2%20-%20Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%202/Optimization_methods_v1b.ipynb) - [Week 3 - PA 5 - TensorFlow Tutorial](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C2%20-%20Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%203/Tensorflow_introduction.ipynb) ### Course 3: Structuring Machine Learning Projects - There are no programming assignments for this course. But this course comes with very interesting case study quizzes (below). ### Course 4: Convolutional Neural Networks - [Week 1 - PA 1 - Convolutional Model: step by step](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%201/Convolution_model_Step_by_Step_v1.ipynb) - [Week 1 - PA 2 - Convolutional Neural Networks: Application](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%201/Convolution_model_Application.ipynb) - [Week 2 - PA 1 - Keras - Tutorial - Happy House](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%202/KerasTutorial/Keras%20-%20Tutorial%20-%20Happy%20House%20v2.ipynb) - [Week 2 - PA 2 - Residual Networks](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%202/ResNets/Residual_Networks.ipynb) - [Week 2 - PA 2 - Transfer Learning with MobileNet](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%202/Transfer%20Learning%20with%20MobileNet/Transfer_learning_with_MobileNet_v1.ipynb) - [Week 3 - PA 1 - Car detection with YOLO for Autonomous Driving](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%203/Car%20detection%20for%20Autonomous%20Driving/Autonomous_driving_application_Car_detection.ipynb) - [Week 3 - PA 2 - Image Segmentation Unet](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%203/Image%20Segmentation%20Unet/Image_segmentation_Unet_v2.ipynb) - [Week 4 - PA 1 - Art Generation with Neural Style Transfer](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%204/Neural%20Style%20Transfer/Art_Generation_with_Neural_Style_Transfer.ipynb) - [Week 4 - PA 2 - Face Recognition](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%204/Face%20Recognition/Face_Recognition.ipynb) ### Course 5: Sequence Models - [Week 1 - PA 1 - Building a Recurrent Neural Network - Step by Step](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%201/Building%20a%20Recurrent%20Neural%20Network%20-%20Step%20by%20Step/Building_a_Recurrent_Neural_Network_Step_by_Step.ipynb) - [Week 1 - PA 2 - Dinosaur Land -- Character-level Language Modeling](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%201/Dinosaur%20Island%20--%20Character-level%20language%20model/Dinosaurus_Island_Character_level_language_model.ipynb) - [Week 1 - PA 3 - Jazz improvisation with LSTM](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%201/Jazz%20improvisation%20with%20LSTM/Improvise_a_Jazz_Solo_with_an_LSTM_Network_v4_Solution.ipynb) - [Week 2 - PA 1 - Word Vector Representation and Debiasing](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%202/Word%20Vector%20Representation/Operations_on_word_vectors_v2a.ipynb) - [Week 2 - PA 2 - Emojify!](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%202/Emojify/Emoji_v3a.ipynb) - [Week 3 - PA 1 - Neural Machine Translation with Attention](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%203/Machine%20Translation/Neural_machine_translation_with_attention_v4a.ipynb) - [Week 3 - PA 2 - Trigger Word Detection](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%203/Trigger%20word%20detection/Trigger_word_detection_v2a.ipynb) - [Week 4 - PA 1 - Transformer Network](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%204/Transformer%20Subclass/C5_W4_A1_Transformer_Subclass_v1.ipynb) - [Week 3 - PA 2 - Transformer Network Application: Named-Entity Recognition](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%203/Named%20Entity%20Recognition/Transformer_application_Named_Entity_Recognition.ipynb) - [Week 3 - PA 2 - Transformer Network Application: Question Answering](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%203/Question%20Answering/QA_transformer.ipynb) ## Quiz Solutions ### Course 1: Neural Networks and Deep Learning - Week 1 Quiz - Introduction to deep learning: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%201/Week%201%20Quiz%20-%20Introduction%20to%20deep%20learning.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%201/Week%201%20Quiz%20-%20Introduction%20to%20deep%20learning.pdf) - Week 2 Quiz - Neural Network Basics: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%202/Week%202%20Quiz%20-%20Neural%20Network%20Basics.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%202/Week%202%20Quiz%20-%20Neural%20Network%20Basics.pdf) - Week 3 Quiz - Shallow Neural Networks: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%203/Week%203%20Quiz%20-%20Shallow%20Neural%20Networks.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%203/Week%203%20Quiz%20-%20Shallow%20Neural%20Networks.pdf) - Week 4 Quiz - Key concepts on Deep Neural Networks: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%204/Week%204%20Quiz%20-%20Key%20concepts%20on%20Deep%20Neural%20Networks.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C1%20-%20Neural%20Networks%20and%20Deep%20Learning/Week%204/Week%204%20Quiz%20-%20Key%20concepts%20on%20Deep%20Neural%20Networks.pdf) ### Course 2: Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization - Week 1 Quiz - Practical aspects of deep learning: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C2%20-%20Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%201/Week%201%20Quiz%20-%20Practical%20aspects%20of%20deep%20learning.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C2%20-%20Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%201/Week%201%20Quiz%20-%20Practical%20aspects%20of%20deep%20learning.pdf) - Week 2 Quiz - Optimization algorithms: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C2%20-%20Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%202/Week%202%20Quiz%20-%20Optimization%20algorithms.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C2%20-%20Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%202/Week%202%20Quiz%20-%20Optimization%20algorithms.pdf) - Week 3 Quiz - Hyperparameter tuning, Batch Normalization, Programming Frameworks: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C2%20-%20Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%203/Week%203%20Quiz%20-%20Hyperparameter%20tuning%2C%20Batch%20Normalization%2C%20Programming%20Frameworks.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C2%20-%20Improving%20Deep%20Neural%20Networks%20Hyperparameter%20tuning%2C%20Regularization%20and%20Optimization/Week%203/Week%203%20Quiz%20-%20Hyperparameter%20tuning%2C%20Batch%20Normalization%2C%20Programming%20Frameworks.pdf) ### Course 3: Structuring Machine Learning Projects - Week 1 Quiz - Bird recognition in the city of Peacetopia (case study): [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C3%20-%20Structuring%20Machine%20Learning%20Projects/Week%201%20Quiz%20-%20Bird%20recognition%20in%20the%20city%20of%20Peacetopia%20(case%20study).md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C3%20-%20Structuring%20Machine%20Learning%20Projects/Week%201%20Quiz%20-%20Bird%20recognition%20in%20the%20city%20of%20Peacetopia%20(case%20study).pdf) - Week 2 Quiz - Autonomous driving (case study): [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C3%20-%20Structuring%20Machine%20Learning%20Projects/Week%202%20Quiz%20-%20Autonomous%20driving%20(case%20study).md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C3%20-%20Structuring%20Machine%20Learning%20Projects/Week%202%20Quiz%20-%20Autonomous%20driving%20(case%20study).pdf) ### Course 4: Convolutional Neural Networks - Week 1 Quiz - The basics of ConvNets: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%201/Week%201%20Quiz%20-%20The%20basics%20of%20ConvNets.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%201/Week%201%20Quiz%20-%20The%20basics%20of%20ConvNets.pdf) - Week 2 Quiz - Deep convolutional models: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%202/Week%202%20Quiz%20-%20Deep%20convolutional%20models.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%202/Week%202%20Quiz%20-%20Deep%20convolutional%20models.pdf) - Week 3 Quiz - Detection algorithms: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%203/Week%203%20Quiz%20-%20Detection%20algorithms.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%203/Week%203%20Quiz%20-%20Detection%20algorithms.pdf) - Week 4 Quiz - Special applications: Face recognition & Neural style transfer: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%204/Week%204%20Quiz%20-%20Special%20applications%20Face%20Recognition%20and%20Neural%20Style%20Transfer.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C4%20-%20Convolutional%20Neural%20Networks/Week%204/Week%204%20Quiz%20-%20Special%20applications%20Face%20Recognition%20and%20Neural%20Style%20Transfer.pdf) ### Course 5: Sequence Models - Week 1 Quiz - Recurrent Neural Networks: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%201/Week%201%20Quiz%20-%20Recurrent%20Neural%20Networks.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%201/Week%201%20Quiz%20-%20Recurrent%20Neural%20Networks.pdf) - Week 2 Quiz - Natural Language Processing & Word Embeddings: [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%202/Week%202%20Quiz%20-%20Natural%20Language%20Processing%20%26%20Word%20Embeddings.pdf) - Week 3 Quiz - Sequence models & Attention mechanism: [Text](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%203/Week%203%20Quiz%20-%20Sequence%20models%20%26%20Attention%20mechanisms.md) | [PDF](https://nbviewer.jupyter.org/github/amanchadha/coursera-deep-learning-specialization/blob/master/C5%20-%20Sequence%20Models/Week%203/Week%203%20Quiz%20-%20Sequence%20models%20%26%20Attention%20mechanisms.pdf) ## Disclaimer I recognize the time people spend on building intuition, understanding new concepts and debugging assignments. The solutions uploaded here are **only for reference**. They are meant to unblock you if you get stuck somewhere. Please do not copy any part of the code as-is (the programming assignments are fairly easy if you read the instructions carefully). Similarly, try out the quizzes yourself before you refer to the quiz solutions. This course is the most straight-forward deep learning course I have ever taken, with fabulous course content and structure. It's a treasure by the deeplearning.ai team.

近期下载者：

相关文件：

评论：[我要评论] [举报此文件]

收藏者：