Overview of 7 Categories of Convolutional Neural Network (CNN) Innovations

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Overview of 7 Categories of Convolutional Neural Network (CNN) Innovations

Click on the above “Beginner’s Guide to Vision”, select to add “Bookmark” or “Pin“ Heavyweight content delivered promptly Image Processing| Computer Vision CV | Deep Learning | Vision Language Model VLM Introduction This review categorizes recent innovations in CNN architectures into seven distinct categories based on spatial utilization, depth, multi-path, width, feature map utilization, channel … Read more

In-Depth! Illustrated Mathematical Principles of Neural Networks

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In-Depth! Illustrated Mathematical Principles of Neural Networks

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

Implementing Fully Connected Neural Networks from Scratch

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Implementing Fully Connected Neural Networks from Scratch

This article introduces the basic concepts in deep learning neural networks: Vectors, Matrices, and Multidimensional Arrays Basics of Neural Networks Activation Functions Implementing Fully Connected Networks from Scratch Mathematics and Python Basics In neural networks, vectors and matrices are ubiquitous. Below is an introduction to creating one-dimensional, two-dimensional, and higher-dimensional arrays using numpy. Vector (One-Dimensional … Read more

A Comprehensive Summary of Graph Neural Networks (GNN)

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A Comprehensive Summary of Graph Neural Networks (GNN)

Originally from Python Artificial Intelligence Frontier Graph Neural Networks are widely used in recommendation systems, knowledge graphs, and traffic road analysis due to their advantages in processing non-Euclidean space data and complex features. However, when the graph data volume increases, problems arise: computation becomes extremely slow, memory cannot hold it, and communication in distributed systems … Read more

6 Types of Neural Networks Every Data Scientist Must Know

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6 Types of Neural Networks Every Data Scientist Must Know

Neural networks are powerful deep learning models capable of synthesizing vast amounts of data in seconds. There are many different types of neural networks that help us accomplish various everyday tasks, from recommending movies or music to assisting us in online shopping. Similar to how airplanes were inspired by birds, neural networks (NNs) are also … Read more

Essential Algorithms in Machine Learning

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Essential Algorithms in Machine Learning

AI Popular Science 18 Essential Algorithms in Machine Learning Neural Networks The 21st century is an information age, as well as a big data age. For traditional methods and tools, processing and analyzing massive amounts of data is a huge challenge. At this time, neural networks emerged as a powerful machine learning tool, demonstrating great … Read more

Illustrated Architecture of Deep Neural Networks

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Illustrated Architecture of Deep Neural Networks

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

Understanding Neural Networks: A Simple Guide

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Understanding Neural Networks: A Simple Guide

This year’s Nobel Prize in Physics was awarded to AI pioneer Hinton, whose major contribution is the invention of a new neural network – the Boltzmann machine, which has shone brightly in the field of machine learning. So what is a neural network? The essence of the large models that have been popular in recent … Read more

Opportunities and Challenges of MoE Large Model Training and Inference

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With the development of large model technology and the proposal of the Scaling Law in 2020, it has become a consensus in the industry to improve model performance by expanding data scale and increasing model parameters. However, current large models face many engineering challenges in training, inference, and application stages. Simply increasing the model size … Read more

The Last Mile of Large Models: A Comprehensive Review of Large Model Evaluation

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The Last Mile of Large Models: A Comprehensive Review of Large Model Evaluation

MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP master’s and doctoral students, university teachers, and researchers from enterprises. The vision of the community is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, especially for beginners. … Read more