Sequences and Prediction-Introduction
Introduction, A conversation with Andrew Ng
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Sequences and Prediction-Sequences and Prediction
Time series examples
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Machine learning applied to time series
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Common patterns in time series
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Introduction to time series
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Where to find the notebooks for this course
Introduction to time series notebook (Lab 1)
Train, validation and test sets
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Metrics for evaluating performance
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Moving average and differencing
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Trailing versus centered windows
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Forecasting
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Forecasting notebook (Lab 2)
Week 1 Wrap up
Sequences and Prediction-Lecture Notes (Optional)
Lecture Notes Week 1
Sequences and Prediction-Weekly Assignment - Create and predict synthetic data
Assignment Troubleshooting Tips
(Optional) Downloading your Notebook and Refreshing your Workspace
Deep Neural Networks for Time Series-Deep Neural Networks for Time Series
A conversation with Andrew Ng
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Preparing features and labels notebook (Lab 1)
Preparing features and labels
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Preparing features and labels (screencast)
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Single layer neural network notebook (Lab 2)
Feeding windowed dataset into neural network
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Single layer neural network
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Machine learning on time windows
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Prediction
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More on single layer neural network
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Deep neural network notebook (Lab 3)
Deep neural network training, tuning and prediction
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Deep neural network
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Week 2 Wrap up
Deep Neural Networks for Time Series-Lecture Notes (Optional)
Lecture Notes Week 2
Recurrent Neural Networks for Time Series-Recurrent Neural Networks for time series
Week 3 - A conversation with Andrew Ng
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Conceptual overview
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RNN notebook (Lab 1)
Shape of the inputs to the RNN
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Outputting a sequence
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Lambda layers
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Adjusting the learning rate dynamically
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More info on Huber loss
LSTM
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Link to the LSTM lesson
LSTM notebook (Lab 2)
Coding LSTMs
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Week 3 Wrap up
Recurrent Neural Networks for Time Series-Lecture Notes (Optional)
Lecture Notes Week 3
Real-world time series data-Real-world time series data
Week 4 - A conversation with Andrew Ng
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Convolutions
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Convolutional neural networks course
Bi-directional LSTMs
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More on batch sizing
Convolutions with LSTM notebook (Lab 1)
Convolutions with LSTM
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Real data - sunspots
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Train and tune the model
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Prediction
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Sunspots notebooks (Lab 2 & Lab 3)
Sunspots
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Combining our tools for analysis
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Real-world time series data-Lecture Notes (Optional)
Lecture Notes Week 4
Real-world time series data-End of Access to Lab Notebooks
[IMPORTANT] Reminder about end of access to Lab Notebooks
Real-world time series data-Course 4 Wrap up
Wrap up
Congratulations!
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Real-world time series data-References and Acknowledgments
References
Acknowledgments
Real-world time series data-TensorFlow in practice has come to an end
Specialization wrap up - A conversation with Andrew Ng
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What next?
(Optional) Opportunity to Mentor Other Learners