There are no reviews yet. Be the first to send feedback to the community and the maintainers!
Machine-Learning-for-Asset-Managers
Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos LΓ³pez de Prado.Machine-Learning-for-Asset-Managers-Oslo-Bors
Deep-learning-for-regression-of-cod-otoliths
Using the EfficientNet family to predict cod-otolith age.Deep-learning-for-salmon-scales
Fish scales constitute a valuable source of information about individual life histories, but correctly extracting this information requires a highly skilled expert. Here, we train a deep convolutional neural network architecture EfficientNet B4 on a set of about 9000 salmon scale images, and show that it attains good performance on predicting a set of variables used in stock management. Further, we see substantial benefits from user transfer learning with a network pre-trained on ImageNet, even if the salmon scale images are very different from those found in the data used for pre-training.Statistics-and-Data-Analysis-for-Financial-Engineering-Copulas
stochasticProcessStat220
The course will consider Markov processes in discrete and continuous time. The theory is illustrated with examples from operation research, biology and economy.Sentiment-Analysis-with-BERT
https://towardsdatascience.com/sentiment-analysis-in-10-minutes-with-bert-and-hugging-face-294e8a04b671demo_Marchenko_Pastur_Analysis
Presentation held at IMR Machine Learning journal club 15. October 2020. Demo Marcenko Pasture distribution applied to eigenvalues of random matrixTime_Series_stat211
This course gives an introduction to linear time series models, such as autoregressive, moving average and ARMA models. Moreover, it is shown how the empirical autocorrelation and partial correlation can be used to identify the model. The Durbin- Levinson, the innovation algorithm and the theory for optimal forecasts are explained. The last part of the course gives an introduction to methods of estimation. Empirical modelling using the AIC and FPE criteria is mentioned as is ARCH and GARCH models.Love Open Source and this site? Check out how you can help us