Welcome to the public repo for this course.

Below is the list of assignments and ungraded labs course-wise.

If you find a bug or typo please raise an issue :)

• Housing Prices (C1W1_Assignment.ipynb)

1. Hello World Neural Network (C1_W1_Lab_1_hello_world_nn.ipynb)

• Handwriting Recognition (C1W2_Assignment.ipynb)

1. Beyond Hello World, A Computer Vision Example (C1_W2_Lab_1_beyond_hello_world.ipynb)
2. Callbacks (C1_W2_Lab_2_callbacks.ipynb)

• Improve MNIST with Convolutions (C1W3_Assignment.ipynb)

1. Improving Accuracy with Convolutions (C1_W3_Lab_1_improving_accuracy_using_convolutions.ipynb)
2. Exploring Convolutions (C1_W3_Lab_2_exploring_convolutions.ipynb)

• Handling Complex Images (C1W4_Assignment.ipynb)

1. Image Generator (C1_W4_Lab_1_image_generator_no_validation.ipynb)
2. Image Generator with Validation (C1_W4_Lab_2_image_generator_with_validation.ipynb)
3. Compacted Images (C1_W4_Lab_3_compacted_images.ipynb)

• Cats vs. Dogs (C2W1_Assignment.ipynb)

1. Using more sophisticated images with Convolutional Neural Networks (C2_W1_Lab_1_cats_vs_dogs.ipynb)

• Cats vs. Dogs using Augmentation (C2W2_Assignment.ipynb)

1. Cats vs. Dogs with Augmentation (C2_W2_Lab_1_cats_v_dogs_augmentation.ipynb)
2. Horses vs. Humans with Augmentation (C2_W2_Lab_2_horses_v_humans_augmentation.ipynb)

• Horses vs. Humans using Transfer Learning (C2W3_Assignment.ipynb)

1. Exploring Transfer Learning (C2_W3_Lab_1_transfer_learning.ipynb)

• Multi-class Classifier (C2W4_Assignment.ipynb)

1. Classifying Rock, Paper, and Scissors (C2_W4_Lab_1_multi_class_classifier.ipynb)

• Explore the BBC News Archive (C3W1_Assignment.ipynb)

1. Simple Tokenizing (C3_W1_Lab_1_tokenize_basic.ipynb)
2. Simple Sequences (C3_W1_Lab_2_sequences_basic.ipynb)
3. Sarcasm (C3_W1_Lab_3_sarcasm.ipynb)

• Categorizing the BBC News Archive (C3W2_Assignment.ipynb)

1. Positive or Negative IMDB Reviews (C3_W2_Lab_1_imdb.ipynb)
2. Sarcasm Classifier (C3_W2_Lab_2_sarcasm_classifier.ipynb)
3. IMDB Review Subwords (C3_W2_Lab_3_imdb_subwords.ipynb)

• Exploring Overfitting in NLP (C3W3_Assignment.ipynb)

1. IMDB Subwords 8K with Single Layer LSTM (C3_W3_Lab_1_single_layer_LSTM.ipynb)
2. IMDB Subwords 8K with Multi Layer LSTM (C3_W3_Lab_2_multiple_layer_LSTM.ipynb)
3. IMDB Subwords 8K with 1D Convolutional Layer (C3_W3_Lab_3_Conv1D.ipynb)
4. IMDB Reviews with GRU (and optional LSTM and Conv1D) (C3_W3_Lab_4_imdb_reviews_with_GRU_LSTM_Conv1D.ipynb)
5. Sarcasm with Bidirectional LSTM (C3_W3_Lab_5_sarcasm_with_bi_LSTM.ipynb)
6. Sarcasm with 1D Convolutional Layer (C3_W3_Lab_6_sarcasm_with_1D_convolutional.ipynb)

• Writing Shakespeare with LSTMs (C3W4_Assignment.ipynb)

1. NLP with Irish Music (C3_W4_Lab_1.ipynb)
2. Generating Poetry from Irish Lyrics (C3_W4_Lab_2_irish_lyrics.ipynb)

• Create and Predict Synthetic Data (C4W1_Assignment.ipynb)

1. Time Series (C4_W1_Lab_1_time_series.ipynb)
2. Forecasting (C4_W1_Lab_2_forecasting.ipynb)

• Predict with a DNN (C4W2_Assignment.ipynb)

1. Preparing Features and Labels (C4_W2_Lab_1_features_and_labels.ipynb)
2. Single Layer Neural Network (C4_W2_Lab_2_single_layer_NN.ipynb)
3. Deep Neural Network (C4_W2_Lab_3_deep_NN.ipynb)

• Using RNN's and LSTM's for time series (C4W3_Assignment.ipynb)

1. Recurrent Neural Network (RNN) (C4_W3_Lab_1_RNN.ipynb)
2. Long Short-Term Memory (LSTM) (C4_W3_Lab_2_LSTM.ipynb)

• Daily Minimum Temperatures in Melbourne - Real Life Data (C4W4_Assignment.ipynb)

1. Long Short-Term Memory (LSTM) (C4_W4_Lab_1_LSTM.ipynb)
2. Sunspots (C4_W4_Lab_2_Sunspots.ipynb)
3. Sunspots - DNN Only (C4_W4_Lab_3_DNN_only.ipynb)