Includes material (code + description) that I turned into notebooks, in connection to our AI and machine learning certifications (see details here). You are free to download and run them in your environment.
In particular:
Interpolation_temperatures_india.ipynb
(geospatial statistics) is a simplified solution, part of project 3.2 in the project textbook.GAN_diabetes.ipynb
(generative adversarial network, diabetes dataset) is part of project 5.2 in the project textbook.sd_vendors
(GAN vendor comparison, evaluation metric, holdout method) is part of project 5.1 in the project textbook.NoGAN.py
(very fast better than GAN synthesizer for tabular data, without neural networks) is part of project 2.1 in the project textbook.Copula_insurance_byGroup.ipynb
andCopula_insurance_nogroup.ipynb
(insurance dataset, tabular data generation with copulas) are related to project 5.2.DeepResampling.ipynb
is a different version of NoGAN. The full name of the method is Hierarchical Deep Resampling (no neural network involved) or NoGAN2. Also very fast and better than GAN, with self-tuning, and explainable AI.
The project textbook is offered to participants in the certification programs. For details about the cost (starting at $44) and how to enroll, see here.