Let’s start with a question. What is the need for an ID generator if databases already offer us with auto-increment IDs? With a single write instance, we may it may not make much sense. But what if we have more than one write instances? How will ensure there is no…

Today let’s demystify the secret behind back-propagation. In this post, I will try to include all Math involved in back-propagation. Familiarity with basic calculus would be great. Otherwise, I don’t recommend continuing this article. Let’s start with what is back-propagation? In simple terms, it computes the derivatives of the loss…

Today let us create a simple two-layered Neural Network using PyTorch. We will be implementing the neural network shown in Figure 1. First, you need to install PyTorch. Check this article of mine for the installation process. Like any other program, we need to import the packages at the beginning. …

Fine-tuning and feature extraction with PyTorch — Introduction to Transfer Learning Transfer Learning is a technique where a model trained for a certain task is used for another similar task. In deep learning, there are two major transfer learning approaches: 1. Fine-tuning: Here, a pre-trained model is loaded and used for training. …

Tensors are the primary data structure used in deep learning, inputs, outputs everything within a neural network is represented using Tensors. So what the heck is a Tensor? The Deep Learning Book says as follows. "In the general case, an array of numbers arranged on a regular grid with a variable number of axes is known as…