How to Classify the paintings of an artist using Convolutional Neural Network
Original Article was published on Data Spoof Blog
In this article, I will explore how we can use Pytorch to solve an image classification problems of multiple classes. Pytorch comes with a lot of tools and libraries that help in solving our problem. Pytorch provides modules in the range from a high level like torch.nn module( It is used for creating neural networks) to low-level autograd functions. Most of the deep learning researchers use the PyTorch framework to do their tasks. Pytorch is written in c++, Python, and Scala language to make our life easier.
Some other blog post that you may want to read is
- Time Series analysis in python part-1
- K-Means Clustering in Python using scikit-learn
- Implementation of K- Nearest Neighbors from scratch in python
- Chapter 1- PyTorch for Beginners: Basics
- Building a logistic regression in Python
Recently I have visited an art gallery where 100 paintings are hanging on their wall. It is very difficult for normal human beings to classify paintings of different artists. So there comes deep learning technology to help in the identification of paintings by different artists.
