dsilt-tsa

Code and materials for the Data Science in Layman's Terms: Time Series Analysis course

Before running any of the code, be sure to install the requirements. Links to the datasets are below.

python -m virtualenv env
source env/bin/activate
python -m pip install -r requirements.txt

Time Series Classification API Service

For the time_series_classification API service, you will need to train the models before starting the API. This can be done by running the evaluation script:

python evaluate_models.py

The API can then be ininialized with:

uvicorn main:app

Go to http://127.0.0.1:8000/docs to try it out.

Links

Links from the lecture slides are listed below, under the name of the lecture they are from.

Autocorrelation

• Create the sine/cosine graphs from the cycles/seasonality slide: https://www.desmos.com/calculator/nqfu5lxaij

Forecasting with Nonlinear Models

• Convolutional neural networks learn different features at different levels: https://indico.io/blog/exploring-computer-vision-convolutional-neural-nets/
• Paper that introduced the transformer: https://arxiv.org/abs/1706.03762

Signals

• Visual explanation of the Fourier Transform: https://www.youtube.com/watch?v=spUNpyF58BY

Anomaly Detection and Forecasting Project

• Kaggle notebook: https://www.kaggle.com/nicholaslincoln/anomaly-detection-forecasting

Segmentation Project

• Kaggle notebook: https://www.kaggle.com/nicholaslincoln/brett-favre-change-point-detection

Sequence Prediction Project

• Maestro MIDI Dataset: https://magenta.tensorflow.org/datasets/maestro
• Transformer Music Generation repo: https://github.com/nlinc1905/transformer-music-generation

Time Series Classification Project

• ECG dataset from Kaggle: https://www.kaggle.com/shayanfazeli/heartbeat
• Paper that describes the dataset and pre-processing steps: https://arxiv.org/pdf/1805.00794.pdf

Signal Processing Project

• LIGO home: https://www.ligo.caltech.edu/
• Dataset source: https://www.gw-openscience.org/catalog/GWTC-1-confident/single/GW150914/
• YouTube video that plays the output wav file: https://www.youtube.com/watch?v=IYq39kCjUns

Time and Location Project

• San Francisco crime data 2003-2018: https://data.sfgov.org/Public-Safety/Police-Department-Incident-Reports-Historical-2003/tmnf-yvry
• San Francisco crime data 2018-present: https://data.sfgov.org/Public-Safety/Police-Department-Incident-Reports-2018-to-Present/wg3w-h783
• GeoJSON for police districts: https://data.sfgov.org/Public-Safety/Current-Police-Districts/wkhw-cjsf

What Else About Time Series

• Data Science in Layman's Terms: Statistics: https://www.amazon.com/Data-Science-Laymans-Terms-Statistics/dp/0692150757
• Quantstart Advanced Algorithmic Trading ebook: https://www.quantstart.com/advanced-algorithmic-trading-ebook/
• Jason Brownlee's time series forecasting book: https://machinelearningmastery.com/introduction-to-time-series-forecasting-with-python/
• Jason Brownlee's guide to data transformation for time series modeling: https://machinelearningmastery.com/time-series-forecasting-supervised-learning/
• Jason Brownlee's guide to data transformation for time series modeling: https://machinelearningmastery.com/convert-time-series-supervised-learning-problem-python/
• My R package for fraud detection with Benford's Law: https://github.com/nlinc1905/benfordsLaw