These notebooks are meant for reference and not for copy pasting the Solution
Introduction to Deep Learning - Coursera
- [Week 1]
- Lesson Topic: Linear regression and classification, Gradient descent, Linear models, Overfiting, Validation, Regularization, Stochastic gradient descent, Optimization
- Quiz: Linear models, Overfiting and Regularization
- Assignment: Linear models and optimization
- [Week 2]
- Lesson Topic: MLP, Chain rule, Backpropagation, Matrix derivatives, TensorFlow framework, Keras,
- Quiz: Multilayer perceptron, Matrix derivatives
- Assignment: MNIST digits classification with TF
- Optional: Your very own neural network
- [Week 3]
- Lesson Topic: Convolutional layers, CNN architecture, Computer Vision tasks
- Quiz: Convolutions and pooling
- Assignment: Your first CNN on CIFAR-10, Fine-tuning InceptionV3 for flowers classification
- [Week 4]
- Lesson Topic: Unsupervised learning, Autoencoders, NLP, Word embeddings
- Quiz: Word embeddings
- Assignment: Simple autoencoder
- Optional: Generative Adversarial Networks
- [Week 5]
- Lesson Topic: Recurrent layers, Simple RNN and Backpropagation, LSTM, GRU, Practical use cases for RNNs
- Quiz: RNN and Backpropagation, Modern RNNs, How to use RNNs
- Assignment: Generating names with RNNs
- [Week 6]
- Lesson Topic: None
- Quiz: None
- Assignment: Image Captioning Final Project