First, let’s visually perceive the status of “Deep Learning”. The image below is a relationship diagram of AI, Machine Learning, and Deep Learning. The field of AI is relatively broad, Machine Learning is a subfield of AI, and Deep Learning is a subset within the Machine Learning domain. Deep learning algorithms have recently become increasingly … Read more
About 8000 words, recommended reading time 20 minutes. This article introduces the mathematical principles behind artificial neural networks. Introduction When it comes to artificial intelligence algorithms, artificial neural networks (ANN) are an unavoidable topic. However, for beginners, it is often easy to be overwhelmed by the complex concepts and formulas in ANN, leading to a … Read more
Click the above “Little White Learns Vision“, choose to add “Starred” or “Top“ Heavyweight content delivered first-hand The optimization of machine learning (objective) can be simply described as: searching for a set of parameters w for the model that can significantly reduce the cost function J(w). This cost function usually includes performance evaluation over the … Read more
Introduction: Here comes the valuable content! Udacity Machine Learning course mentor Walker is here to teach you how to understand neural networks in a simple, vivid, and interesting way! What is a neural network? A neural network is a series of simple nodes that, when combined simply, express a complex function. Let’s explain each one … Read more
First, let’s visually appreciate the position of “Deep Learning”. The following diagram illustrates the relationship between AI, Machine Learning, and Deep Learning. The field of AI is relatively broad, with Machine Learning being a subfield of AI, and Deep Learning being a subset within the Machine Learning domain. Deep learning algorithms have recently become increasingly … Read more
Why is Machine Learning Necessary? Some tasks are complex to encode directly; we cannot handle all the nuances and simple coding. Therefore, machine learning is essential. Instead, we provide a large amount of data to machine learning algorithms, allowing them to explore the data and build models to solve problems. For example: recognizing 3D objects … Read more
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
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
Large models are showing an explosive growth trend (more parameters / greater computational power requirements). With the continuous advancement of algorithm and computational technologies, large models will further evolve into more advanced and powerful versions, being applied in an increasing number of fields to generate more beautiful dialogues and content for humanity. Source: Xinhua News … Read more
This article is reprinted from the public account Brother Biao has something to say Source: Internet Below is a comprehensive glossary of 725 machine learning terms compiled by several authoritative experts in machine learning, which is very comprehensive and worth collecting! English Term Chinese Translation 0-1 Loss Function 0-1 Loss Function Accept-Reject Sampling Method Accept-Reject … Read more