Sequences, Time Series and Prediction

This folder contains jupyter notebooks for the exercises in Coursera course: Sequences, Time Series and Prediction, part of the DeepLearning.AI TensorFlow Developer Professional Certificate. This course demonsrates the use of RNNs and Tensorflow in time series modeling.

Table of Contents

- Simple statistical techniques such as moving average, see W1_Naive_Movingavg,ipynb.

- Simple RNN for prediction, see W2_RNN.ipynb.

- LSTM layer, see W3_LSTM.ipynb.

- Add a Conv1D layer, see W4_AddConv1D.ipynb.

W1-W3 use synthetic data generated in the .ipynb. W4 uses real data 'daily-min-temperatures.csv' in the folder.