PyTorch

Going through the Workflow of a PyTorch ProjectPhoto by Igor Lepilin on UnsplashIn this article, we will go through the lifecycle of a Deep Learning project using PyTorch. We assume that you are already familiar with Neural Networks and will not explain them in detail, but only consider the PyTorch-specific aspects. We will mainly follow the steps shown in the official documentation of PyTorch, but consider a different example. In the documentation an example of image classification is presented, here we will consider…

Too Long; Didn't ReadThe two most widely-used open-source machine learning frameworks for training and building deep learning models are TensorFlow and PyTorch. These frameworks have unique differences in their approach to building and training models. The choice of frameworks depends on the user's specific needs and preferences. This article looks at the Best PyTorch Datasets for Building Deep Learning Models. Too Long; Didn't ReadThe two most widely-used open-source machine learning frameworks for training and…

Table of Contents Introduction Installation of dependencies  and importing of Blenderbot model Chatting with the model Conclusion References Introduction In Artificial Intelligence, Blenderbot comes under the category of conversational agents. A conversational agent, or CA, is a computer program designed to have a conversation with a person, according to Wikipedia. In other words, conversational agents are automated systems — often driven by artificial intelligence — that are designed to have natural-language…

Understanding the theory and implementation of custom loss functions in PyTorch using the MNIST datasetPhoto by Markus Winkler on UnsplashIntroductionIn machine learning, the loss function is a critical component that measures the difference between the predicted output and the actual output. It plays a vital role in the training of a model, as it guides the optimization process by indicating the direction in which the model should improve. The choice of loss function depends on the specific task and the data type. In…

What is PyTorch? PyTorch is a deep learning open-source TensorFlow library that is based on the well-known Torch library. It's also a Python-based library that is more commonly used for natural language processing and computer vision. In this tutorial, we will be using PyTorch to train our model for Text Classification. What Is Hugging Face? Hugging Face is an open-source dataset (website) provider which is used mainly for its natural language processing (NLP) datasets among others. It contains tons of valuable…

Dissecting the `nn.Embedding` layer in PyTorch and a complete guide on how it worksOpenAI DALL-E Generated ImageYou might have seen the famous PyTorch nn.Embedding() layer in multiple neural network architectures that involves natural language processing (NLP). This is one of the simplest and most important layers when it comes to designing advanced NLP architectures. Let me explain what it is, in simple terms.After spending some time looking into its C++ source code, here is what I found. The nn.Embedding layer is a…

Using DeepShap to understand and improve the model powering an autonomous car(source: author)Autonomous cars terrify me. Big hunks of metal flying around with no humans to stop them if something goes wrong. To reduce this risk it is not enough to evaluate the models powering these beasts. We also need to understand how they are making predictions. This is to avoid any edge cases that would cause unforeseen accidents.Okay, so our application is not so consequential. We will be debugging the model used to power a…

A Step-by-Step Guide to training a Word2vec ModelPhoto by Brett Jordan on UnsplashAn important component of natural language processing (NLP) is the ability to translate words, phrases, or larger bodies of text into continuous numerical vectors. There are many techniques for accomplishing this task, but in this post we will focus in on a technique published in 2013 called word2vec.Word2vec is an algorithm published by Mikolov et al. in a paper titled Efficient Estimation of Word Representations in Vector Space. This paper…

Using YOLOv5 in PyTorch YOLO, an acronym for 'You only look once,' is an open-source software tool utilized for its efficient capability of detecting objects in a given image in real time. The YOLO algorithm uses convolutional neural network (CNN) models to detect objects in an image.  The algorithm requires only one forward propagation through a given neural network to detect all objects in the image. This gives the YOLO algorithm an edge in speed over others, making it one of the most well-known detection…

Last Updated on November 28, 2022 Linear regression is a statistical technique for estimating the relationship between two variables. A simple example of linear regression is to predict the height of someone based on the square root of the person’s weight (that’s what BMI is based on). To do this, we need to find the slope and intercept of the line. The slope is how much one variable changes with the change in other variable by one unit. The intercept is where our line crosses with the $y$-axis. Let’s use the simple…