add a developers guide

docs/freqai-developers.md

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+# Development 
+
+The class structure and details algorithmic overview is depicted in the following diagram: 
+
+![image](assets/freqai_algorithm-diagram.jpg)
+
+As shown, there are three distinct objects comprising `FreqAI`:
+
+* IFreqaiModel
+  * Singular persistent object containing all the necessary logic to collect data, store data, process data, engineer features, run training, and inference models. 
+* FreqaiDataKitchen
+  * A non-persistent object which is created uniquely for each unique asset/model. Beyond metadata, it also contains a variety of data processing tools. 
+* FreqaiDataDrawer
+  * Singular persistent object containing all the historical predictions, models, and save/load methods. 
+
+There are a variety of built-in prediction models which inherit directly from `IFreqaiModel` including:
+
+* CatboostRegressor
+* CatboostRegressorMultiTarget
+* CatboostClassifier
+* LightGBMRegressor
+* LightGBMRegressorMultiTarget
+* LightGBMClassifier
+* XGBoostRegressor
+* XGBoostRegressorMultiTarget
+* XGBoostClassifier
+
+Each of these have full access to all methods in `IFreqaiModel`. And can therefore, override any of those functions at will. However, advanced users will likely stick to overriding `fit()`, `train()`, `predict()`, and `data_cleaning_train/predict()`.