master: Adding links to table of contents.

Author: purvasingh96

README.md

@@ -7,13 +7,122 @@ This repository contains -<br>
 :heavy_check_mark: Summarized notes on Udacity's **Nanodegree in AI** ([Bertelsmann Scholarship](https://www.udacity.com/bertelsmann-tech-scholarships))<br>
 
 The images in this repository are taken from Udacity's Deep Learning Nanodegree program.
-## Contributor
+
+# Repository Content: Projects and Theorey List
+
+Over the course of time, I have enrolled in multiple MOOCs and read multiple books related to Deep Learning. I try to document all the important notes in one place so that it is easy for me to revise :). Below are the list of projects/theorey that I have worked on/documented. Please see the **Project List** for the code and refer the **Theorey List** for the detailed explaination of various concepts.:
+## Project List
+
+1. [Recap of Numpy and Matrices](./Chapter-wise code/Code%20-%20PyTorch/0.%20Recap%20Numpy%20and%20Matrices)
+    * [Quiz on Numpy](./Chapter-wise%20code/Code%20-%20PyTorch/0.%20Recap%20Numpy%20and%20Matrices/NumPy_Quiz.py)
+    * [Scalars, Vectors, Matrices, Tensors](./Chapter-wise%20code/Code%20-%20PyTorch/0.%20Recap%20Numpy%20and%20Matrices/Scalars,_Vectors,_Matricies_and_Tensors.ipynb)
+    
+2. [Introduction to PyTorch](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch)
+    * [Deep Learning with PyTorch - 60 minute blitz](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/01.%20Deep_Learning_with_PyTorch_A_60_Minute_Blitz_.ipynb)
+    * [Verify PyTorch Installation](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/01.verify_pytorch_installation.ipynb)
+    * [Autograd Automatic Differentiation](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/02.%20Autograd_Automatic_Differentiation.ipynb)
+    * [Single Layer Neural Network](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/02.single_layer_neural_network.ipynb)
+    * [Neural Networks](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/03.%20Neural_networks.ipynb)
+    * [Multi-layer Neural Networks](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/03.mutilayer_neural_network.ipynb)
+    * [Implementing Softmax Function](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/04.implementing_softmax.ipynb)
+    * [Training an Image Classifier](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/04_Training_an_image_classifier.ipynb)
+    * [Implementing ReLU Activation Function via PyTorch](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/05.ReLU_using_pytorch.ipynb)
+    * [Playing with TensorBoard](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/05_Playing_with_TensorBoard.ipynb)
+    * [Training Neural Network via PyTorch](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/06.training_neural_network_via_pytorch.ipynb)
+    * [Validation via PyTorch](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/07.%20Validating_using_pytorch.ipynb)
+    * [Regularization via PyTorch](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/08.%20Regularization_using_pytorch.ipynb)
+    * [Loading Image Data via PyTorch](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/09.%20loading_image_data_via_pytorch.ipynb)
+    * [Transfer Learning via PyTorch](./Chapter-wise%20code/Code%20-%20PyTorch/1.%20Intro%20to%20PyTorch/10.%20Transfer_learning_via_pytorch.ipynb)
+ 
+3. [Convolutional Neural Networks](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks)
+    * [Basics: Load, Train, Test and Validate your Model](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/1.%20Basics/Load_train_test_and_validate_your_model.ipynb)
+    * [CIFAR Image Classification](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/2.%20Image%20Classification/CIFAR_image_classifier.ipynb)
+    * [Object Detection](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/3.%20Object%20Detection)
+        * [Frontal Face Recognition](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/3.%20Object%20Detection/frontal_face_recognition.ipynb)
+        * [Object Detection](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/3.%20Object%20Detection/Object_Detection.ipynb)
+    * [Transfer Learning](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/4.%20Transfer%20Learning)
+        * [Bees Prediction via Transfer Learning](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/4.%20Transfer%20Learning/Transfer_Learning_predict_bees.ipynb)
+        * [Flower Prediction via Transfer Learning](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/4.%20Transfer%20Learning/Transfer_Learning_predict_flowers.ipynb)
+    * [Style Transfer](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/5.%20Style%20Transfer)
+        * [Style Transfer on an Octopus](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/5.%20Style%20Transfer/style_transfer_on_octopus.ipynb)
+        * [Style Transfer on Purva](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/5.%20Style%20Transfer/style_transfer_on_purva.ipynb)
+    * [Data Augmentation](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/6.%20Data%20augmentation)
+    * [Weight Initialization Strategies](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/7.%20Weight%20Initialization%20Strategies/Weight_initialization.ipynb)
+    * [Autoencoders](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/8.%20Autoencoders)
+        * [Linear Autoencoder](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/8.%20Autoencoders/linear_autoencoder.ipynb)
+        * [Convolutional Autoencoder](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/8.%20Autoencoders/convolution_autoencoder.ipynb)
+    * [Dog Breed Classifier](./Chapter-wise%20code/Code%20-%20PyTorch/2.%20Convolution%20Neural%20Networks/9.%20Dog%20breed%20classifier)
+    
+ 4. [Recurrent Neural Networks](./Chapter-wise%20code/Code%20-%20PyTorch/3.%20Recurrent%20Neural%20Networks)
+    * [Text Generation using RNNs](./Chapter-wise%20code/Code%20-%20PyTorch/3.%20Recurrent%20Neural%20Networks/1.%20Text%20generation%20using%20RNNs)
+        * [Future Anna Karenina Series](./Chapter-wise%20code/Code%20-%20PyTorch/3.%20Recurrent%20Neural%20Networks/1.%20Text%20generation%20using%20RNNs/future_anna_karenina.ipynb)
+        * [Future Harry Potter Series](./Chapter-wise%20code/Code%20-%20PyTorch/3.%20Recurrent%20Neural%20Networks/1.%20Text%20generation%20using%20RNNs/future_harry_potter_series.ipynb)
+    * [Sentiment Analysis](./Chapter-wise%20code/Code%20-%20PyTorch/3.%20Recurrent%20Neural%20Networks/2.%20Sentiment%20Analysis/sentiment_analysis.ipynb)
+    * [Time Series Prediction](./Chapter-wise%20code/Code%20-%20PyTorch/3.%20Recurrent%20Neural%20Networks/3.%20Time%20Series%20Prediction)
+    * [Word2Vec](./Chapter-wise%20code/Code%20-%20PyTorch/3.%20Recurrent%20Neural%20Networks/4.%20Word2Vec)
+    * [Generation of T.V. Scripts via NLG](./Chapter-wise%20code/Code%20-%20PyTorch/3.%20Recurrent%20Neural%20Networks/5.%20Generate%20TV%20Scripts)
+    * [Attention](./Chapter-wise%20code/Code%20-%20PyTorch/3.%20Recurrent%20Neural%20Networks/6.%20Attention/Readme.md)
+ 
+ 5. [Generative Adversarial Networks (GANs)](./Chapter-wise%20code/Code%20-%20PyTorch/4.%20Generative%20Adversarial%20Networks%20(GANs))
+    * [Overview: Theorey](./Chapter-wise%20code/Code%20-%20PyTorch/4.%20Generative%20Adversarial%20Networks%20(GANs)/Readme.md)
+    * [Generate Hand Written Digits using GANs](./Chapter-wise%20code/Code%20-%20PyTorch/4.%20Generative%20Adversarial%20Networks%20(GANs)/1.%20Generating%20hand-written%20digits%20using%20GANs/Hand_written_digit_generation_via_GANs.ipynb)
+    * [Deep Convolutional GANs](./Chapter-wise%20code/Code%20-%20PyTorch/4.%20Generative%20Adversarial%20Networks%20(GANs)/2.%20Deep%20Convolution%20GANs/Deep_Convolution_GANs.ipynb)
+    * [Cyclic GANs](./Chapter-wise%20code/Code%20-%20PyTorch/4.%20Generative%20Adversarial%20Networks%20(GANs)/3.%20Cyclic%20GANs/Readme.md)
+        * [Image-to-Image Translation via Cyclic GANs](./Chapter-wise%20code/Code%20-%20PyTorch/4.%20Generative%20Adversarial%20Networks%20(GANs)/3.%20Cyclic%20GANs/Image-to-Image%20Translation%20via%20Cyclic%20GANs/Image_to_image_translation_via_Cyclic_GANs.ipynb)
+    * [Generating Faces via DCGAN](./Chapter-wise%20code/Code%20-%20PyTorch/4.%20Generative%20Adversarial%20Networks%20(GANs)/4.%20Generate%20Faces%20via%20DCGAN/dlnd_face_generation.ipynb)
+    
+ 6. [Deploying Sentiment Analysis Model using Amazon Sagemaker](./Chapter-wise%20code/Code%20-%20PyTorch/5.%20Deploy%20Models%20to%20PROD%20via%20Amazon%20Sagemaker)
+    * [Deploy IMDB Sentiment Analysis Model](./Chapter-wise%20code/Code%20-%20PyTorch/5.%20Deploy%20Models%20to%20PROD%20via%20Amazon%20Sagemaker/1.%20Deploy%20IMDB%20Sentiment%20Analysis%20Model/IMDB%20Sentiment%20Analysis%20-%20XGBoost%20-%20Web%20App.ipynb)
+    * [Deploy Your Own Sentiment Analysis Model](./Chapter-wise%20code/Code%20-%20PyTorch/5.%20Deploy%20Models%20to%20PROD%20via%20Amazon%20Sagemaker/2.%20Deploy%20your%20own%20sentiment%20analysis%20model/SageMaker%20Project.ipynb)
+    
+ 7. [Natural Language Processing](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing)
+    * [Naive Bayes Spam Classifier](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/1.%20Naive%20Bayes%20Spam%20Classifier/spam_classifier/Bayesian_Inference.ipynb)
+    * [POS Tagging](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/2.%20Parts%20of%20Speech%20Tagging/Readme.md)
+        * [HMMs for POS Tagging](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/2.%20Parts%20of%20Speech%20Tagging/HMM%20Tagger.ipynb)
+    * [Feature Extraction and Embeddings](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/3.%20Feature%20Extraction%20&%20Embeddings/Readme.md)
+    * [Topic Modelling](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/4.%20Topic%20Modelling/Readme.md)
+    * [Latent Dirichlet Allocation](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/4.%20Topic%20Modelling/Latent_dirichlet_allocation.ipynb)
+    * [Sentiment Analysis](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/5.%20Sentiment%20Analysis)
+        * [BERT for sentiment analysis of Twits (StockTwits)](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/5.%20Sentiment%20Analysis/bert-for-sentiment-analysis-of-stock-twits.ipynb)
+        * [EDA and sentiment analysis of COVID-19 tweets](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/5.%20Sentiment%20Analysis/covid19-tweets-eda-and-sentiment-analysis.ipynb)
+        * [EDA and sentiment analysis of Joe Biden's tweets](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/5.%20Sentiment%20Analysis/eda-and-sentiment-analysis-of-joe-biden-tweets.ipynb)
+    * [Machine Translation](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/6.%20Machine%20Translation/Readme.md)
+        * [English to French](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/6.%20Machine%20Translation/machine_translation.ipynb)
+    * [Speech Recognition](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/7.%20Speech%20Recognition/vui_notebook.ipynb)
+
+8.  [Natural Language Generation](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/8.%20Natural%20Language%20Generation)
+    * [Text generation via RNNs and (Bi)LSTMs](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/8.%20Natural%20Language%20Generation/text-generation-via-rnn-and-lstms-pytorch.ipynb)
+
+9. [Question Answering Models](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/9.%20Question%20Answering)
+    * [BERT for answering queries related to stocks](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/9.%20Question%20Answering/bert-for-answering-queries-related-to-stocks.ipynb)
+
+10. [Text Classification](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/10.%20Text%20Classification/)
+    * [Github bug prediction using BERT](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/10.%20Text%20Classification/github-bug-prediction-via-bert.ipynb)
+    * [Predicting DJIA movement using BERT](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/10.%20Text%20Classification/predicting-DJIA-movement-with-BERT.ipynb)
+    * [SMS spam classifier](./Chapter-wise%20code/Code%20-%20PyTorch/6.%20Natural-Language-Processing/10.%20Text%20Classification/sms-spam-classifier.ipynb) 
+        
+## Theorey List
+This list basically contains summarized notes for each chapter from the book, 'Deep Learning' by 'Goodfellow, Benigo and Courville':
+
+1. [Chapter 1: Linear Algebra](./Chapter-wise%20notes/Ch_1_Linear_algebra/Readme.md)
+2. [Chapter 2: Probability and Information Theorey](./Chapter-wise%20notes/Ch_2_Probability_and_Information_Theorey/Readme.md)
+3. [Chapter 3: Numerical Computation](./Chapter-wise%20notes/Ch_3_Numerical_Computation/ReadMe.md)
+4. [Chapter 4: Machine Learning Basics](./Chapter-wise%20notes/Ch_4_Machine_Learning_Basics/ReadMe.md)
+5. [Chapter 5: Deep Forward Networks](./Chapter-wise%20notes/Ch_5_Deep_Forward_Networks/ReadMe.md)<br>
+    5.1.[Chapter 5.1: Back Propogation](./Chapter-wise%20notes/Ch_5_Deep_Forward_Networks/Ch_5.1_Back_Propagation/Readme.md)
+6. [Chapter 6: Regularization for Deep Learning](./Chapter-wise%20notes/Ch_6_Regularization_for_Deep_Learning/Readme.md)
+7. [Chapter 7: Optimization for Training Deep Models](./Chapter-wise%20notes/Ch_7_Optimization_for_training_deep_models/Readme.md)
+8. [Chapter 8: Convolutional Neural Networks](./Chapter-wise%20notes/Ch_8_Convolutional_Neural_Networks/Readme.md)
+9. [Chapter 9: Reccurent Neural Networks](./Chapter-wise%20notes/Ch_9_Recurrent_Neural_Networks/Readme.md)<br>
+    9.1 [Chapter 9.1: LSTMs](./Chapter-wise%20notes/Ch_9_Recurrent_Neural_Networks/LSTM.md)
+
+# Contributor
 - [Purva Singh](https://purvasingh96.github.io)
 
-## Contributing
+# Contributing
 
 Please feel free to open a Pull Request to contribute towards this repository. Also, if you think there's any section that requires more/better explanation, please use the issue tracker to let me know about the same.
 
-## Support 
+# Support 
 
 If you like this repo and find it useful, please consider (★) starring it (on top right of the page) so that it can reach a broader audience.