Archives for overfitting
Through this post we will discuss about overfitting and methods to use to prevent the overfitting of a neural network.
The post 5 methods that will not let your neural network model overfit appeared first on Analytics India Magazine.
Overfitting is a basic problem which could be mitigated at various stages of machine learning project.
The post Steps to perform when your machine learning model overfits in training appeared first on Analytics India Magazine.
Whenever a data scientist works to predict or classify a problem, they first detect accuracy by using the trained model to the train set and then to the test set. If the accuracy is satisfactory, i.e., both the training and testing accuracy are good, then a particular model is considered for further development. But sometimes,…
The post Understanding Overfitting and Underfitting for Data Science appeared first on Analytics India Magazine.
A machine learning model is only as good as the data it’s trained on. In other words, the poor performance of a model is mainly due to overfitting and underfitting. Overfitting happens when the model is modelled ‘too well’ on the training data. Underfitting refers to a model that can neither model the training data…
The post Why Is Overfitting So Demonized? appeared first on Analytics India Magazine.
Imagine this scenario — you have tested your machine learning model well, and you get absolutely perfect accuracy. Happy with a job well done, and then decide to deploy your project. However, when the actual data is applied to this model, you get poor results. So, why did this happen? The possible reason for this…
The post What is Data Leakage in ML & Why Should You Be Concerned appeared first on Analytics India Magazine.
In this article, we will:
Learn the different techniques to avoid overfitting of the model and Implement these techniques to a deep learning model
The post How To Avoid Overfitting In Neural Networks appeared first on Analytics India Magazine.
In this article, we will demonstrate why data augmentation is known as a regularization technique. How to apply data augmentation to our model and whether it is used as a preprocessing technique or post-processing techniques...? All these questions are answered in this demonstration.
The post Why Does Image Data Augmentation Work As A Regularizer in Deep Learning? appeared first on Analytics India Magazine.