In Machine Learning, we sometimes use models trained and developed by other developers for some complex tasks. These models are known as pre-trained model. It is not a bad idea to use a pre-trained model for solving a similar problem for which the model was developed and made available. In this article, I will take you through what are pre-trained models in machine learning.
What are Pre Trained Models?
In Machine Learning, a pre-trained model falls under the category of transfer learning. Pre Trained models are machine learning models that are trained, developed and made available by other developers. They are generally used to solve problems based on deep learning and are always trained on a very large dataset.
They are made available by developers who want to contribute to the machine learning community to solve a similar problem. The way so many developers contribute to the community by creating frameworks and packages the same way some developers also contribute with a machine learning model which is known as a Pre Trained model. These models are generally made for solving very complex and common problems. LeNet-5, AlexNet, GoogLeNet are some of the popular pre-trained models.
Examples of a Pre Trained Model
Most of the pre-trained models that have been built and made available till now are based on convolutional neural networks. Below are some of the examples of such models that you can use:
- LeNet-5:Â This is one of the most widely used convolutional neural network architectures. It was created by Yann LeCunn in 1998 and it is very much used for the task of recognizing handwritten digits.
- AlexNet:Â It won the 2012 ImageNet challenge by a very large margin. It achieved a top-five error rate of 17% where the second-best achieved an error rate of 26%. It is very similar to LeNet-5.
- GoogLeNet:Â It was developed by Christian Szegedy et al. from Google Research. This model has 10 times fewer parameters than AlexNet, roughly around 6 million instead of 60 million.
Also, Read – 200+ Machine Learning Projects Solved and Explained.
Summary
So a pre-trained model is a model developed and made available by other developers for solving very complex problems which are very common in the machine learning community. Such models are mostly based on convolutional neural networks. I hope you liked this article on what is a pre-trained model in machine learning. Feel free to ask your valuable questions in the comments section below.
