Regularization in Machine Learning is an important concept and it solves the overfitting problem. It is very important to understand regularization to train a good model. Sometimes one resource is not enough to get you a good understanding of a concept. I have learnt regularization from different sources and I feel learning from different sources is very important. An easy and simple explanation is what everyone needs. I am listing 2 Quora answers and 5 articles, I hope, these will help.

Thank you for reading. If you want to get into contact, you can reach out to me at ahikailash1@gmail.com

About Me:

I am a Co-Founder of MateLabs, where we have built Mateverse, an ML Platform which enables everyone to easily build and train Machine Learning Models, without writing a single line of code.

Note: Recently, I published a book on GANs titled “Generative Adversarial Networks Projects”, in which I covered most of the widely popular GAN architectures and their implementations. DCGAN, StackGAN, CycleGAN, Pix2pix, Age-cGAN, and 3D-GAN have been covered in details at the implementation level. Each architecture has a chapter dedicated to it. I have explained these networks in a very simple and descriptive language using Keras framework with Tensorflow backend. If you are working on GANs or planning to use GANs, give it a read and share your valuable feedback with me at ahikailash1@gmail.com