* refactor(Naming): use `primary_models` & `meta_labeling_models`
* refactor(Naming): using primary * meta_labeling across config and in pipeline
* feat(Pipeline): added back Ensemble models
* fix(Pipeline): compiler error
* fix(Config): typo
* chore(Pipeline): removed unused averaging step
* revert the changes in discretizing
* chore(Pipeline): remove sharpe improvement logging
* fix(Pipeline): ensemble predictions should be a pd.Series instead of a DataFrame
* fix(Pipeline): discard unnecessary ensemble_probabilities
* fix(Pipeline): fixes regarding various meta-labeling ensemble bugs
* fix(Reporting): use the new naming convention
* fix(Reporting): use the right variable
* feat(Sweep): new sweep for ensemble models
* fix(Sweep): config reference
* fix(Config): simplified dev config
* fix(Models): use the faster LR model
* fix(Models): use LGBM in the meta-labeling model for speed
* fix(Selection): always use the first model for feature selection, commented out caching from select_features() as it's close to redundant in terms of speed
* feat(DataLoader): added load_only_returns() method
* feat(Portfolio): load predictions
* feat(Portfolio): normalize weights
* feat(Portfolio): started integrating with portfoliobt
* feat(Portfolio): include fees in the portfolio construction
* feat(Portfolio): demo of pyportfolioopt
* feat(Portfolio): get efficient frontier calculation to work
* feat(Portfolio): add a few strategies to create weights
* chore(Dependencies): remove pyportfolioopt for now
* fix(Dependencies): try to install all dependencies with pip
* fix(Dependencies): indentation
* fix(Dependencies): corrected pytorch module name
* fix(Dependencies): try to have as many modules installed by conda for the sake of sanity?
* fix(Dependencies): put fracdiff into pip modules
* fix(Dependencies): revert to using pip almost exclusively
* feat(Portfolio): added alphalens
* fix(Portfolio): got limited weights working
* feat(Portfolio): trying to get alphalens to work
* feat(Portfolio): alphalens working
* fix(Dependencies): removed vectorbt
* fix(Dependencies): use alphalens-reloaded
* fix(Dependencies): added conda source for alphalens-reloaded
* refactor(Portfolio): removed traces of vectorbt
* feat(Reporting): factor reporting done
* feat(Portfolio): added pyfolio reporting (fails bc alphalens is not working properly lol)
Mark Aron Szulyovszky