All the time divide your data into training, validation, and testing sets.It occurs when your model learns the training data too well, a lot in order that it fails to generalize to unseen data. Overfitting is the bogeyman under the bed for each beginner in deep learning. You fed it a lot out of your training data, it couldn’t recognize anything.” Heartbroken, Alex sought Emma’s advice, to which she replied, “You’ve fallen for the Overfitting Monster. The model performed miserably on latest data. Elated, Alex shared his model with a senior colleague, Emma, just for her to return the subsequent day with bad news. In his enthusiasm, he trained a posh neural network that might predict the stock market with startling accuracy. Once upon a time, there was a rookie data scientist named Alex, desperate to apply his newly-acquired deep learning skills.
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