notebooks
ML notebooks
Differential machine learning implementation and demonstration notebooks
Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.
138 stars
15 watching
51 forks
Language: Jupyter Notebook
last commit: over 2 years ago
Linked from 1 awesome list
aadautomatic-differentiationbackpropagationcomputational-financedeep-learningderivativesmachine-learningnotebookspricingquantitative-financeregression-modelsrisk-magazinerisk-managementtensorflow
Related projects:
Repository | Description | Stars |
---|---|---|
| A collection of Python machine learning code accompanying a finance textbook. | 1,873 |
| A collection of incomplete machine learning experiments in Jupyter Notebooks | 566 |
| Repository providing example notebooks for Deep Learning applications with TensorFlow and Earth Engine. | 76 |
| A runtime environment for machine learning via Jupyter notebooks. | 32 |
| Experimental solutions to selected exercises from the book Advances in Financial Machine Learning by Marcos Lopez De Prado | 1,722 |
| A collection of Python notebooks focused on quantitative finance and derivatives pricing using the QuantLib library. | 151 |
| Automated machine learning for production and analytics | 1,642 |
| An implementation of Manning Publications' How Machine Learning Works book in Python using Jupyter Notebook | 4 |
| The codebase provides MATLAB implementations of machine learning concepts from S. Theodoridis' book | 66 |
| Teaching materials and resources for a Machine Learning course in finance at NYU Tandon | 373 |
| An all-in-one web-based IDE for machine learning and data science | 3,446 |
| An autoML framework for building and analyzing trading systems and sports betting models using machine learning algorithms. | 1,170 |
| A tutorial on parallel machine learning with scikit-learn and IPython | 1,593 |
| A comprehensive resource for machine learning and deep learning algorithms | 295 |
| Automated deep learning algorithm that performs feature engineering, model selection, and hyperparameter tuning without human intervention. | 1,140 |