GrokkingDeepLearning

This repository will contain my take on Andrew Trask's book GrokkingDeepLearning.

The way you should go about fidgeting the repository:

Forward Propagation
Gradient Descent (which also takes into account the learning concept in the neural network)
Generalizing Gradient Descent
MNIST dataset with weight visualization
MNIST dataset with weight visualization using Keras
StreetLight Problem, introducing the concept of input to output correlation
Streetlight Problem, making an intermediate layer for a Deep Neural Network.
Convolution as a structure to reuse weights
Convolutional Neural Network
Sentiment analysis using the IMDB Review DATASET

Name		Name	Last commit message	Last commit date
Latest commit History 34 Commits
assets		assets
#10_SentimentIMDB.ipynb		#10_SentimentIMDB.ipynb
#1_ForwardProp.ipynb		#1_ForwardProp.ipynb
#2_GradientDescent.ipynb		#2_GradientDescent.ipynb
#3_GeneralizingGradientDescent.ipynb		#3_GeneralizingGradientDescent.ipynb
#4_MNISTWeightVisualization.ipynb		#4_MNISTWeightVisualization.ipynb
#5_MNISTWeightVisualizationKeras.ipynb		#5_MNISTWeightVisualizationKeras.ipynb
#6_StreetlightProblemCorrelationOfInputToOutput.ipynb		#6_StreetlightProblemCorrelationOfInputToOutput.ipynb
#7_StreetlightProblemDeepNeuralNetwork.ipynb		#7_StreetlightProblemDeepNeuralNetwork.ipynb
#8_Convolutions.ipynb		#8_Convolutions.ipynb
#9_Convolution_NN.ipynb		#9_Convolution_NN.ipynb
.gitignore		.gitignore
README.md		README.md