Update README.md

Author: sudharsan13296

README.md

@@ -44,66 +44,66 @@ By the end of this book, you will be equipped with the skills you need to implem
 
 ## Table of contents 
 
-### [1. Introduction to Deep Learning](#)
+### [1. Introduction to Deep Learning](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/tree/master/01.%20Introduction%20to%20Deep%20Learning)
 
-* [1.1. What is Deep Learning?](#)
+* [1.1. What is Deep Learning?](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/01.%20Introduction%20to%20Deep%20Learning/1.01%20What%20is%20Deep%20Learning%3F.ipynb)
 * 1.2. Biological and Artifical Neurons
 * 1.3. ANN and its Layers
 * 1.4. Exploring Activation Functions
 * 1.5. Forward Propagation in ANN
 * 1.6. How does ANN learn?
 * 1.7. Debugging Gradient Descent with Gradient Checking 
 * 1.8. Putting it all together
-* [1.9. Building Neural Network from Scratch](#)
+* [1.9. Building Neural Network from Scratch](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/01.%20Introduction%20to%20Deep%20Learning/1.09%20Building%20Neural%20Network%20from%20scratch.ipynb)
 
 
-### [2. Getting to Know TensorFlow](#)
+### [2. Getting to Know TensorFlow](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/tree/master/02.%20Getting%20to%20Know%20TensorFlow)
 
 * 2.1. What is TensorFlow?
 * 2.2. Understanding Computational Graphs and Sessions
 * 2.3. Variables, Constants, and Placeholders
 * 2.4. Introducing TensorBoard
-* [2.5. Handwritten digits classification using Tensorflow ](#)
+* [2.5. Handwritten digits classification using Tensorflow ](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/02.%20Getting%20to%20Know%20TensorFlow/2.05%20Handwritten%20digits%20classification%20using%20TensorFlow.ipynb)
 * 2.6. Visualizing Computational graph in TensorBord
 * 2.7. Introducing Eager execution
-* [2.8. Math operations in TensorFlow](#)
-* [2.9. Tensorflow 2.0 and Keras](#)
-* 2.10. MNIST digits classification in Tensorflow 2.0
-* 2.11. Should we use Keras or TensorFlow?
+* [2.8. Math operations in TensorFlow](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/02.%20Getting%20to%20Know%20TensorFlow/2.08%20Math%20operations%20in%20TensorFlow.ipynb)
+* 2.9. Tensorflow 2.0 and Keras
+* [2.10. MNIST digits classification in Tensorflow 2.0](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/02.%20Getting%20to%20Know%20TensorFlow/2.10%20MNIST%20digits%20classification%20in%20TensorFlow%202.0.ipynb)
+* [2.11. Should we use Keras or TensorFlow?](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/02.%20Getting%20to%20Know%20TensorFlow/2.11%20Should%20we%20use%20Keras%20or%20TensorFlow%3F.ipynb)
 
 
 
-### [3. Gradient Descent and its variants](#)
+### [3. Gradient Descent and its variants](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/tree/master/03.%20Gradient%20Descent%20and%20its%20variants)
 
-* [3.1. Demystifying Gradient Descent](#)
-* [3.2. Performing Gradient Descent in Regression](#)
+* [3.1. Demystifying Gradient Descent](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/03.%20Gradient%20Descent%20and%20its%20variants/3.01%20Demystifying%20Gradient%20Descent.ipynb)
+* [3.2. Performing Gradient Descent in Regression](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/03.%20Gradient%20Descent%20and%20its%20variants/3.02%20Performing%20Gradient%20Descent%20in%20Regression.ipynb)
 * 3.3. Gradient Descent vs Stochastic Gradient Descent
 * 3.4. Momentum based Gradient Descent
 * 3.5. Adaptive methods of Gradient Descent
-* [ 3.6. Implementing Various Gradient descent methods from Scratch](#)
+* [ 3.6. Implementing Various Gradient descent methods from Scratch](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/03.%20Gradient%20Descent%20and%20its%20variants/3.06%20%20Implementing%20Several%20Variants%20of%20Gradient%20Descent%20from%20Scratch.ipynb)
 
 
 
-### [4. Generating Song lyrics with RNN](#)
+### [4. Generating Song lyrics with RNN](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/tree/master/04.%20Generating%20Song%20Lyrics%20Using%20RNN)
 
 
-* [4.1. Hola Recurrent Neural Networks](#)
+* [4.1. Hola Recurrent Neural Networks](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/04.%20Generating%20Song%20Lyrics%20Using%20RNN/4.01%20Hola%20Recurrent%20Neural%20Networks.ipynb)
 * 4.2. Forward Propagation in RNN 
 * 4.3. Backpropagation through time (BPTT) 
 * 4.4. Deriving BPTT step by step
 * 4.5. Vanishing and Exploding Gradients
-* [4.6. Generating song lyrics using RNN](#)
+* [4.6. Generating song lyrics using RNN](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/04.%20Generating%20Song%20Lyrics%20Using%20RNN/4.06%20Generating%20Song%20Lyrics%20Using%20RNN.ipynb)
 * 4.7. Different types of RNN architectures
 
 
-### [5. Improvements to the RNN](#)
+### [5. Improvements to the RNN](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/tree/master/05.%20Improvements%20to%20the%20RNN)
 
-* [5.1. LSTM to the Rescue](#)
+* 5.1. LSTM to the Rescue
 * 5.2. Understanding the LSTM cell
 * 5.3. Forward propagation in LSTM
 * 5.4. Backpropagation in LSTM
 * 5.5. Deriving backpropagation of LSTM Step by step
-* [5.6. Predicting Bitcoins price using LSTM](#)
+* [5.6. Predicting Bitcoins price using LSTM](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/05.%20Improvements%20to%20the%20RNN/5.06%20Predicting%20Bitcoins%20price%20using%20LSTM%20RNN.ipynb)
 * 5.7. Gated Recurrent Units
 * 5.8. Understanding GRU cell
 * 5.9. Forward propagation in GRU cell
@@ -114,84 +114,84 @@ By the end of this book, you will be equipped with the skills you need to implem
 * 5.14. Language Translation Seq2seq models
 
 
-### [6. Demystifying Convolutional Networks](#)
+### [6. Demystifying Convolutional Networks](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/tree/master/06.%20Demystifying%20Convolutional%20Networks)
 
 * 6.1. What is CNN?
 * 6.2. Architecture of CNN
 * 6.3. Math of CNN 
-* [ 6.4. Implementing CNN in tensorflow](#)
+* [ 6.4. Implementing CNN in tensorflow](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/06.%20Demystifying%20Convolutional%20Networks/6.04%20Implementing%20CNN%20in%20TensorFlow.ipynb)
 * 6.5. Different types of CNN architectures
 * 6.6. Capsule networks
-* [6.7. Building capsule networks in Tensorflow](#)
+* [6.7. Building capsule networks in Tensorflow](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/06.%20Demystifying%20Convolutional%20Networks/6.07%20Building%20Capsule%20Networks%20in%20TensorFlow.ipynb)
 
 
-### [7. Learning Text Representations](#)
+### [7. Learning Text Representations](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/tree/master/07.%20Learning%20Text%20Representations)
 
-* 7.1. Understanding Word2vec Model
+* [7.1. Understanding Word2vec Model](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/07.%20Learning%20Text%20Representations/7.01%20Understanding%20Word2vec%20Model.ipynb)
 * 7.2. Continuous Bag of words
 * 7.3. Math of CBOW
 * 7.4. Skip- Gram model
 * 7.5. Math of Skip-Gram 
 * 7.6. various training strategies
-* [ 7.7. Building word2vec model using Gensim](#)
-* [7.8. Visualizing word embeddings in TensorBoard](#)
+* [ 7.7. Building word2vec model using Gensim](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/07.%20Learning%20Text%20Representations/7.07%20Building%20word2vec%20model%20using%20Gensim.ipynb)
+* [7.8. Visualizing word embeddings in TensorBoard](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/07.%20Learning%20Text%20Representations/7.08%20Visualizing%20Word%20Embeddings%20in%20TensorBoard.ipynb)
 * 7.9. Converting documents to vectors using doc2vec
-* [7.10. Finding similar documents using Doc2vec](#)
+* [7.10. Finding similar documents using Doc2vec](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/07.%20Learning%20Text%20Representations/7.10%20Finding%20similar%20documents%20using%20Doc2Vec.ipynb)
 * 7.11. Understanding skip thoughts algorithm
 * 7.12 Quick thoughts for sentence embeddings
 
 
-### [8. Generating Images using GANs](#)
+### [8. Generating Images using GANs](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/tree/master/08.%20Generating%20Images%20using%20GANs)
 
-* 8.1. Distinguishing generative and discriminative models
+* [8.1. Distinguishing generative and discriminative models](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/08.%20Generating%20Images%20using%20GANs/8.04%20Demystifying%20GAN%20Loss%20Function.ipynb)
 * 8.2. Say hello to GANs
 * 8.3. Architecture of GANs
 * 8.4. Demystifying GAN loss function
-* [8.5. Generating images using GAN in TensorFlow](#)
+* [8.5. Generating images using GAN in TensorFlow](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/08.%20Generating%20Images%20using%20GANs/8.05%20Generating%20images%20using%20GAN%20in%20TensorFlow.ipynb)
 * 8.6. DCGAN - Adding convolution to the GAN
-* [8.7. Implementing DCGAN to generate CIFAR images](#)
+* [8.7. Implementing DCGAN to generate CIFAR images](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/08.%20Generating%20Images%20using%20GANs/8.07%20Implementing%20DCGAN%20to%20Generate%20CIFAR%20Images.ipynb)
 * 8.8. Least Squares GAN
-* [8.9. Building LSGAN in tensorflow](#)
+* [8.9. Building LSGAN in tensorflow](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/08.%20Generating%20Images%20using%20GANs/8.09%20Building%20LSGAN%20in%20TensorFlow.ipynb)
 * 8.10. WGAN - GANs with Wasserstein distance
 
 
-### [9. Learning more about GANs](#)
+### [9. Learning more about GANs](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/tree/master/09.%20Learning%20more%20about%20GANs)
 
 * 9.1. Conditional GAN 
-* [9.2. Generating specific digits using CGAN](#)
+* [9.2. Generating specific digits using CGAN](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/09.%20Learning%20more%20about%20GANs/9.02%20Generating%20Specific%20Handwritten%20Digit%20Using%20CGAN.ipynb)
 * 9.3. Understanding InfoGAN 
 * 9.4. Architecture of InfoGAN
-* [9.5. Constructing InfoGAN in tensorflow](#)
+* [9.5. Constructing InfoGAN in tensorflow](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/09.%20Learning%20more%20about%20GANs/9.05%20Constructing%20InfoGan%20in%20Tensorflow.ipynb)
 * 9.6. Translating images using CycleGAN
-* [9.7. Converting photos to paintings using CycleGAN](#)
+* [9.7. Converting photos to paintings using CycleGAN](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/09.%20Learning%20more%20about%20GANs/9.07%20Converting%20photos%20to%20paintings%20using%20CycleGAN.ipynb)
 * 9.8. Text to image synthesis using Stack GAN
 
 
-### [10. Reconstructing inputs using Autoencoders](#)
+### [10. Reconstructing inputs using Autoencoders](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/tree/master/10.%20Reconsturcting%20Inputs%20using%20Autoencoders)
 
 * 10.1. What is Autoencoder?
 * 10.2. Understanding the architecture of autoencoders
-* [10.3. Reconstructing MNIST images using autoencoders](#)
+* [10.3. Reconstructing MNIST images using autoencoders](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/10.%20Reconsturcting%20Inputs%20using%20Autoencoders/10.03%20Reconstructing%20MNIST%20images%20using%20Autoencoder.ipynb)
 * 10.4. Autoencoders with convolution
-* [10.5. Building convolution autoencoder](#)
+* [10.5. Building convolution autoencoder](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/10.%20Reconsturcting%20Inputs%20using%20Autoencoders/10.05%20Building%20Convolutional%20Autoencoder.ipynb)
 * 10.6. Exploring denoising autoencoder
-* [10.7. Denoising images using DAE](#)
+* [10.7. Denoising images using DAE](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/10.%20Reconsturcting%20Inputs%20using%20Autoencoders/10.07%20Denoising%20images%20using%20Denoising%20Autoencoder.ipynb)
 * 10.8. Understanding sparse autoencoders
-* [10.9. Building sparse autoencoders](#)
+* [10.9. Building sparse autoencoders](#https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/10.%20Reconsturcting%20Inputs%20using%20Autoencoders/10.09%20Building%20the%20Sparse%20Autoencoder.ipynb
 * 10.10. Learning to use contractive autoencoders
-* [10.11. Implementing contractive autoencoders](#)
+* [10.11. Implementing contractive autoencoders](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/10.%20Reconsturcting%20Inputs%20using%20Autoencoders/10.11%20Implementing%20Contractive%20Autoencoders.ipynb)
 * 10.12. Dissecting variational autoencoders
-* [10.13. Generating images using VAE](#)
+* [10.13. Generating images using VAE](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/10.%20Reconsturcting%20Inputs%20using%20Autoencoders/10.13%20Generating%20images%20using%20VAE.ipynb)
 
 
 
 
-### [11. Exploring few-shot learning algorithms](#)
+### [11. Exploring few-shot learning algorithms](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/tree/master/11.%20Exploring%20Few%20Shot%20Learning%20Algorithms)
 
-* [11.1. What is few-shot learning?](#)
+* [11.1. What is few-shot learning?](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/11.%20Exploring%20Few%20Shot%20Learning%20Algorithms/11.01%20What%20is%20few-shot%20learning%3F.ipynb)
 * 11.2. Understanding Siamese Networks?
 * 11.3. Prototypical Networks
 * 11.4. Relation Networks
 * 11.5. Matching Networks
 * 11.6. Architecture of Matching networks
-* [11.7. What's Next?](#)
+* [11.7. What's Next?](https://github.com/sudharsan13296/Hands-On-Deep-Learning-Algorithms-with-Python/blob/master/11.%20Exploring%20Few%20Shot%20Learning%20Algorithms/11.07%20What's%20Next%3F.ipynb)