Nowadays, after becoming proficient in using dedicated frameworks and high-level libraries like Keras, TensorFlow, or PyTorch, we no longer need to frequently worry about the size of neural network models or remember formulas for activation functions and derivatives. With these libraries and frameworks, creating a neural network, even one with a complex architecture, often only … Read more
Click the "Xiaobai Learns Vision" above, select "Star" or "Pin" Heavy content delivered to you first Author丨Piotr Migdał Source丨Youer’s Cabin Editor丨Jishi Platform Jishi Guide Illustrated overview of the entire neural network architecture, and tools and techniques for understanding specific modules. Baseline Model AlexNet is a groundbreaking architecture that made Convolutional Neural Networks (CNNs) the main … Read more
Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered first! Written by | Lao Tao (Researcher from a certain company, hereditary parameter tuning) Translated by | Beautiful person with meticulous thoughts Introduction As the hottest topic in NLP over the past two years, the language pre-training technologies represented by ELMo/BERT are already familiar … Read more
Click the top “MLNLP” to select the “Starred” public account. Heavyweight content delivered first-hand. From:Number Theory Legacy The prerequisite knowledge for this article includes:Recurrent Neural NetworksRNN, Word EmbeddingsWordEmbedding, Gated UnitsVanillaRNN/GRU/LSTM. 1 Seq2Seq Seq2Seq is the abbreviation for sequence to sequence. The first sequence is called the encoder encoder, which is used to receive the source … Read more
Click on the above“Beginner’s Guide to Vision” to select “Star” or “Pin” Heavyweight content delivered first time From | Zhihu Author | Jixing Link | https://zhuanlan.zhihu.com/p/147885624 Editor | Deep Learning Matters WeChat Official Account This article is for academic exchange only. If there is any infringement, please contact us for deletion. Introduction In recent years, … Read more
Click the above “Beginner’s Guide to Vision“, select to add “Star” or “Top“ Heavyweight content delivered first time Author: Savaram Ravindra Source: mindmajix.com Image recognition is a fascinating and challenging research field. This article elaborates on the concepts, applications, and techniques of convolutional neural networks for image recognition. What is Image Recognition and Why Use … Read more
Click I Love Computer Vision to star and get the latest CVML technologies faster This article is reprinted from Machine Heart. Selected from Medium Author:Ajinkya Khalwadekar Translated by Machine Heart Contributors:Panda, Egg Sauce In the fields of machine learning and computer vision, Optical Character Recognition (OCR) and Handwritten Text Recognition (HTR) have long been important … Read more
MLNLP community is a well-known machine learning and natural language processing community in China and abroad, covering NLP master’s and doctoral students, university teachers, and corporate researchers. The community’s vision is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning, especially for beginners. Reprinted from | … Read more
Source: Python Data Science This article is approximately 7200 words long and is recommended to be read in 14 minutes. In this article, we will explore the Transformer model and understand how it works. 1. Introduction The BERT model launched by Google achieved SOTA results in 11 NLP tasks, igniting the entire NLP community. One … Read more
Source: CSDN Blog Author: Jay Alammar This article is about 7293 words, suggested reading time 14 minutes。 This article introduces knowledge related to the Transformer, using a simplified model to explain core concepts one by one. The Transformer was proposed in the paper “Attention is All You Need” and is now recommended as a reference … Read more