Donald

How to deploy model from Juypter Notebook?

Programming

Following this post, I have trained a model using the online Juypter Notebook. 
My question is how can I deploy the model for backtest? 
I also read this post, but I don't find how to save my model from Juypter Notebook to "/lib"?

Any further guidance from the community will be helpful! 

1 0
Posted on : 2022-07-29 02:21:03.717000
 
admin

Hi Donald, suppose we built a SVC model in the online Jupyter Notebook, it can done as follows:


1. Save model to your library directory (refer to line #10-14)


img1

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from sklearn.svm import SVC
from joblib import dump, load
import os

x = [[2,3,1],[4,6,3]]
y = [1,0]
clf = SVC()
clf.fit(x, y)

# get my /lib directory
pathlib = os.path.dirname(os.getcwd())+"/lib"

# save model to /lib/model_2.m
dump(clf, pathlib+"/model_2.m")

2. Execute the code above, "model_2.m" will then be dumped to your cloud directory /lib.

img2


3. Go to "backtest", load your model from "self.evt.path_lib" (refer to line #15). After that, the model can be used for prediction throughout the backtest process (refer to line #23-25).

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from AlgoAPI import AlgoAPIUtil, AlgoAPI_Backtest
from sklearn.svm import SVC
from joblib import dump, load


class AlgoEvent:
    def __init__(self):
        pass

    def start(self, mEvt):
        # start backtest
        self.evt = AlgoAPI_Backtest.AlgoEvtHandler(self, mEvt)

        # load my model_2.m
        self.model = joblib.load(self.evt.path_lib+"model_2.m")

        self.evt.start()

    def on_marketdatafeed(self, md, ab):
        # use self.model for new market data feed ...

        # model test dataset and print result
        x_test = [[1,2,3],[4,5,6]]
        result = self.model.predict(x_test)
        self.evt.consoleLog(result)

        pass

1 0
Posted on : 2022-07-29 08:49:08.309000



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