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Deep learning has dominated the field of machine learning and artificial intelligence. But why? The reason is that it is simple so that many non-professionals can learn how to work with it in a short amount of time, and yet it is very effective, capable of solving problems that by no means was possible using classic methods.
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It is important to use a separate validation dataset from the train and test sets for tuning model hyperparameters. (ref)
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Ensemble is the art of combining diverse set of learners (Individual models) together to improvise on the stability and predictive power of the model. Roughly, ensemble learning methods, that often trust the top rankings of many machine learning competitions are based on the hypothesis that combining multiple models together can often produce a much more powerful model. Ensemble learning is a machine learning paradigm where multiple models (often called “weak learners”) are trained to solve the same problem and combined to get better results. Click for more info.
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Claim: Any deep learning classifier is a form of logistic regression. Click to see the reasoning behind this.
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There are many different algorithms in the machine learning universe. Each algorithm has its own intuition, use, advantages, and disadvantages. Click for more info.