Click the above“Beginner’s Guide to Vision”, select to add “Star” or “Top” Important content delivered promptly <<Beginner’s Guide to PyTorch>> Reference Directory: 1 Matrix and Scalar 2 Hadamard Product 3 Matrix Multiplication 4 Power and Square Root 5 Logarithmic Operations 6 Approximation Operations 7 Clamping Operations This lesson mainly explains some operations in PyTorch, including … Read more
Click above Datartisan Data Craftsman You can subscribe! Artificial Neural Networks (ANN) are algorithms developed based on the brain’s processing mechanism to establish complex patterns and predictive problems. First, let’s understand how the brain processes information: In the brain, there are billions of neuron cells that process information in the form of electrical signals. External … Read more
Machine Heart Column Author: Liu Zhongyu Source: Geetest (geetest_jy) Today I want to share with you about Graph Convolutional Networks. With the development of artificial intelligence, many people have heard of concepts such as machine learning, deep learning, and convolutional neural networks. However, Graph Convolutional Networks are not often mentioned. So, what are Graph Convolutional … Read more
Selected from Analytics Vidhya Author:Pranav Dar Translated by Machine Heart Contributors: Chen Yunzhu, Lu This article introduces 25 open deep learning datasets, including those for image processing, natural language processing, speech recognition, and real-world problem datasets. Introduction The key to deep learning (or most fields in life) is practice. You need to practice solving various … Read more
Accelerating Development of New Quality Productivity Empowered by AI Models: Internal Mechanisms, Real Obstacles, and Practical Approaches （Huang Zaisheng） Abstract:In the era of digital intelligence, the iterative upgrade and accelerated implementation of AI models represented by ChatGPT are igniting a “knowledge-based productivity revolution,” which has had a wide and profound impact on human production and … Read more
Abstract: Training deep models has been a long-standing challenge. In recent years, a series of methods represented by hierarchical and layer-wise initialization have brought hope to training deep models and have achieved success in various application fields. The parallelization framework and training acceleration methods for deep models are important cornerstones for deep learning to become … Read more
In fact, artificial intelligence has been part of our lives for a long time. However, for many people, artificial intelligence is still a relatively “profound” technology,but no matter how profound the technology is, it starts from basic principles.. There are ten major algorithms in the field of artificial intelligence, which are simple in principle, discovered … Read more
Core Points:A comprehensive summary of machine learning concepts, highly recommended for collection! Hi, I am Cos Dazhuang! Machine learning is divided into two main categories based on model types: supervised learning models and unsupervised learning models. 1. Supervised Learning Supervised learning typically uses training data with expert-labeled tags to learn a function mapping from input … Read more
Machine learning is divided into two main categories based on model types: supervised learning models and unsupervised learning models. 1. Supervised Learning Supervised learning typically uses training data with expert-labeled tags to learn a function mapping from input variable X to output variable Y. Y = f(X), and the training data is usually in the … Read more
Author: Daniel Bourke Published on: 06/06/2020 Translator: Fang Xingxuan This article is 5600 words long and is recommended to be read in 10 minutes. This article summarizes the pre-exam preparation and answers to questions that may arise during the exam based on the author’s experience of taking the TensorFlow certification exam. Tags: Machine Learning | … Read more