DL for Financial Time Series Data
The repository's goal is to developed and explore the usage of DL models on Financial TS Data. It will be consist of different resources used for development, packages for easy data attainment to develop the models on, and a set of notebooks containing models that are either based on existing papers or papers currently being written by the research team running the repo. More precisely, this repository will consist of:
- Relevant papers to these implementations
- A package for data attainment and dataset creation for the Learning Algo
- Daily Financial Time Series Data
- Finacial Statments Data
- The model implemented and notebooks for example implementations
- Targeted OMAML
- Descret Experet Machines
- Reinforcment Learning
- Bayesian Sparsity
- BMAML