A series of interactive lab notebooks we prepared for the DFVA and AZEK Chartered Financial Data Scientist (CFDS) ® Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.
This is currently work in progress so please expect minor errors and some rough edges ;)
Lab 00: "Testing the CFDS Lab Environment"
(Launch Notebook: Binder, Open In Colab)
Lab 01: "Introduction to the CFDS Lab Environment"
(Launch Notebook: Binder, Open In Colab)
Lab 02: "Fundamentals of Python Programming"
(Launch Notebook: Binder, Open In Colab)
Lab 03: "Financial Data Science - Moving Average Trading Strategies"
(Launch Notebook: Binder, Open In Colab)
Lab 04: "Financial Data Science - Mean Reversion Trading Strategies"
(Launch Notebook: Binder, Open In Colab)
Lab 05: "Supervised Machine Learning - Naive Bayes"
(Launch Notebook: Binder, Open In Colab)
Lab 06: "Supervised Machine Learning - k Nearest-Neighbors"
(Launch Notebook: Binder, Open In Colab)
Lab 07: "Supervised Machine Learning - Support Vector Machines"
(Launch Notebook: Binder, Open In Colab)
Lab 09: "Unsupervised Machine Learning - k-Means Clustering"
(Launch Notebook: Binder, Open In Colab)
Lab 10: "Unsupervised Machine Learning - Expectation Maximization Clustering"
(Launch Notebook: Binder, Open In Colab)
Lab 11: "Supervised Deep Learning - Artificial Neural Networks"
(Launch Notebook: Binder, CPU: Open In Colab, GPU: Open In Colab)
Lab 12: "Supervised Deep Learning - Convolutional Neural Networks (CNNs)"
(Launch Notebook: Binder, Open In Colab)
Lab 13: "Unsupervised Deep Learning - Autoencoder Neural Networks (AENs)"
(Launch Notebook: Binder, Open In Colab)
Lab 14: "Supervised Deep Learning - Recurrent Neural Networks (RNNs) (One-To-One)"
(Launch Notebook: Binder, Open In Colab)
Lab 15: "Supervised Deep Learning - Recurrent Neural Networks (RNNs) (Many-To-One)"
(Launch Notebook: Binder, Open In Colab)
Install dependencies via pip install -r requirements.txt.
Please feel free to get in touch by opening an issue report, submitting a pull request, or sending us an email.