Visually probe the behavior of trained machine learning models, with minimal coding.

We gather data, preprocess it, choose a model, train the model and evaluate the predictions; that’s a basic Machine Learning pipeline. Based on the results, we retrain the models for improvement, and hence, it’s an iterative process. The evaluation of models is highly dependent on the data we have. In the case of limited data, we are unable to evaluate the model across a wide range of inputs. But how great would it be if we could test our system in hypothetical situations without having to write too…

Aqsa Kausar

Tuning my hyper-parameters everyday to dive deeper into the foray of deep learning.

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