Slava Kurilyak

@ucalyptus I agree. Using [Google Earth Engine](https://earthengine.google.com/), we can use [geometric operations](https://developers.google.com/earth-engine/geometric_operations) to create buffers, centroid, or bounding boxes for mineral occurrence coordinates. For example, here are the coordinates (38°48′N, ...

@ucalyptus feel free to explore this project in order to predict mineral deposits. Here are a few resources you can check out to build upon your land cover classification work:...

@bukosabino Let's use [pypbo](https://github.com/esvhd/pypbo), the python library, to prevent backtest overfitting

Yes! Let's use technical analysis (ta-lib) as features (see #64) for machine learning.

> I'm working on adding technical analysis features. I am looking forward to it > [This](https://medium.com/catalyst-crypto/leveraging-the-enigma-data-marketplace-to-boost-catalyst-strategies-628082acda4f) article could be useful for us in order to add more features. Thanks for...

Let's add non-pricing datasets as features. We can use cryptocurrency volume data, Blockchain Info, and Google Search Volume.

> I have added some external data sources (Google Search Volume and Blockchain Info) as features for Machine Learning models. Excellent! Since we now have multiple machine learning models, let's...

Excellent work! Now we can combine all of our existing datasets, including: 1. google dataset (see [manager.py#L243](https://github.com/produvia/cryptocurrency-trading-platform/blob/develop/kryptos/platform/data/manager.py#L243)) (use google search terms: "btc usd" associated with the btc/usd cryptoasset), 2. quandl...

@bukosabino Let's use XGBoost to predict the direction of btc_usdt for Bittrex or Poloniex.

I think we can create a strategy object triggered by `$ strat -ml xgboost`. Once the strategy is working as expected, we can define the JSON config via `xgboost.json` @treethought...