Deep Learning-Basics

The notebook is a detailed cookbook on how to create a basic deep neural network (DNN) and a basic convolution neural network (CNN) using keras library and the MNIST datatset. The dataset source is shared in the notebook.

CNN_Data_Augmentation

This notebook is a coursera exercise on how to perform data augmentation with tensorflow and then train a CNN model.

TensorFlow 2.0 Tutorial

The notebook is a tutorial to get started with the basics of TensorFlow 2.0 along with some intermediate level concepts including model subclassing using keras.

References:

1. https://machinelearningmastery.com/handwritten-digit-recognition-using-convolutional-neural-networks-python-keras/
2. https://towardsdatascience.com/building-a-deep-learning-model-using-keras-1548ca149d37
3. https://keras.io/api/layers/
4. https://cs231n.github.io/convolutional-networks/#conv
5. https://poloclub.github.io/cnn-explainer/#article-convolution
6. https://betterexplained.com/articles/intuitive-convolution/
7. https://setosa.io/ev/image-kernels/
8. https://www.tensorflow.org/overview