![10 Cool Things You Can Do With Embeddings! [Part 1]](https://i3.wp.com/miro.medium.com/v2/resize:fit:700/1*JUXKFFHjjSfkG4pxDoeLCQ.png?w=700&resize=700,365&ssl=1 "10 Cool Things You Can Do With Embeddings! [Part 1]")
10 Cool Things You Can Do With Embeddings! [Part 1]
Author(s): Zubia Mansoor Originally published on Towards AI. Apply these concepts to solve real-world industry problems in deep learning Taking a step away from classical machine learning (ML), embeddings are at the core of most deep learning (DL) use cases. Having a …
How to Extract Key Information from Business Documents using LayoutLMv3
Author(s): Nour Islam Mokhtari Originally published on Towards AI. A quick guide on how to use LayoutLMv3 to streamline business documents, understanding This member-only story is on us. Upgrade to access all of Medium. To receive deep insights just like this and …
How to Speedup Inference by Up to 9x on a x86 CPU with Pytorch
Author(s): Nour Islam Mokhtari Originally published on Towards AI. The complete guide on how to achieve some impressive results with a few lines of code! This member-only story is on us. Upgrade to access all of Medium. Image generated using StableDiffusion To …
Graph Attention Networks Paper Explained With Illustration and PyTorch Implementation
Author(s): Ebrahim Pichka Originally published on Towards AI. A detailed and illustrated walkthrough of the βGraph Attention Networksβ paper by VeliΔkoviΔ et al. with the PyTorch implementation of the proposed model. Illustration of the message-passing layer in a Graph Attention Network sβ …
The ABCs of PyTorch in 4 Minutes
Author(s): Rohit Sharma Originally published on Towards AI. PyTorch 101 U+007C Towards AI Introducing the basics of PyTorch in four minutes, with sample code Β© AITS (www.ai-techsystems.com) This article helps newbies to get started with python PyTorch in 2 minutes with code …
Image Classification using Deep Learning & PyTorch: A Case Study with Flower Image Data
Author(s): Avishek Nag Originally published on Towards AI. Classifying Flower images using Convolutional Deep Neural Network with PyTorch library Photo by Krystina rogers on Unsplash Classifying image data is one of the very popular usages of Deep Learning techniques. In this article, …
Number Plate Detection β DETECTRON v2
Author(s): Luka Chkhetiani Originally published on Towards AI. Most (well, at least some) of the βSmart Camerasβ donβt use number plate detection & recognition systems, but they pay attention to specific hidden codes on the number plates, and by sticking some transparent …
Generate Quotes with Web Scrapping, Glove Embeddings, and LSTM in Pytorch
Author(s): Lakshmi Narayana Santha Originally published on Towards AI. Introduction With the rise of advancement in research in NLP specially in Language Models, text generation – a classical machine learning task which solved using Recurrent Networks. In this article we walk through …
Supermasks: A Simple Introduction and Implementation in PyTorch
Author(s): Kourosh T. Baghaei Originally published on Towards AI. The general understanding of neural networks is that computations are required in order to adjust the weights of a neural network so that it could perform a certain task on a given dataset. …
Letβs See How a Computer Seesβ¦
Author(s): Pratik Originally published on Towards AI. Deep Learning, Programming Photo by Robina Weermeijer on Unsplash In humans, there are multiple stages to understand visual information, and the computer also follows this process. Letβs now try to zoom in a bit on …
PyTorch Lightning: An Introduction to the Lightning-Fast Deep Learning Framework
Author(s): Anay Dongre Originally published on Towards AI. PyTorch Lightning is a popular open-source framework built on top of PyTorch that aims to simplify and streamline the process of developing deep learning models. It provides a lightweight and flexible interface for building …
AlexNet: Implementation from Scratch
Author(s): Muhammad Arham Originally published on Towards AI. A PyTorch series for people starting with Deep Learning. Following an implementation-based approach of various well-known architectures. Image from Paper Introduction The Alexnet architecture was a breakthrough at the time of its publication, achieving …
Gradient Checkpointing
Author(s): Harshit Sharma Originally published on Towards AI. To βscaleβ new heights in model training Gradient Checkpointing (aka Re-compute technique/activation checkpointing) is an approach that trades compute for memory and is helpful in scenarios where the available GPU memory is not enough …
Time Series Regression Using Transformer Models: A Plain English Introduction
Author(s): Ludovico Buizza Originally published on Towards AI. A plain English brief introduction to time series data regression/classification and transformers, as well as an implementation in PyTorch Photo by Jason Richard on Unsplash I am working on a project that uses transformer …
Overcoming Catastrophic Forgetting: A Simple Guide to Elastic Weight Consolidation
Author(s): Yunzhe Wang Originally published on Towards AI. image by Midjourney The Problem of Catastrophic Forgetting In the field of artificial intelligence, deep learning models, especially neural networks, have shown great success in a wide range of applications. However, one major challenge …
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