RunByAI

Tag: 机器学习

31 post(s)

October 7, 20260 comment(s)

Introduction to Attention Mechanism: How Transformers "Focus on Key Points"

Why do we need attention mechanismsNot every word is equally important when dealing with a sentence or text. Traditional recurrent neural networks (RNNs) read in sequence one by one, relying on a "mem

Tech Guide 机器学习

October 7, 20260 comment(s)

Introduction to Regularization: How AI Models Prevent "rote memorization"

What is regularizationIn machine learning, overfitting is one of the most common and hidden problems: the model performs nearly perfectly on training data, and it is obviously inaccurate when encounte

Tech Guide 机器学习

October 7, 20260 comment(s)

Introduction to Dimensionality Reduction: How PCA and t-SNE Flatten High Dimensional Data

Why reduce dimensionsReal data often has dozens, hundreds, or even thousands of features: a small image has thousands of pixels, and a text vector may have hundreds of dimensions. As the dimensionalit

Tech Guide 机器学习

October 7, 20260 comment(s)

Introduction to Clustering: How Unsupervised Learning "Clusters Like Things"

What is clusteringClustering is a type of unsupervised learning method that does not have labels and only groups samples that look similar based on their similarity. It is different from classificatio

Tech Guide 机器学习

October 6, 20260 comment(s)

Introduction to Explainable AI (XAI): Why AI Decisions Need to Be Explained

A large model rejected a loan application, but couldn't explain why; A medical imaging model marked the lesion, but the doctor didn't know what it was "seeing". As AI becomes increasingly involved in

Tech View 机器学习 AI Ethics

October 5, 20260 comment(s)

Introduction to Few Shot Learning: How AI learns new tasks with "a few examples"

Traditional deep learning models typically require thousands of annotated samples to learn a task well. But humans are different: just by looking at two or three photos of unfamiliar animals, you can

Tech Guide 机器学习

October 5, 20260 comment(s)

Introduction to Ensemble Learning: How AI Combines Many Models to Predict Better

What is ensemble learningThe idea behind ensemble learning is simple: instead of relying on a single model, train a group of models and combine their outputs. A single model tends to fail in certain w

Tech Guide 机器学习

October 5, 20260 comment(s)

Introduction to Anomaly Detection: How AI Spots the Odd One Out in Data

What is anomaly detectionAnomaly detection, also called outlier detection, aims to find the samples in a large dataset that differ from the majority. Those samples may be early signs of equipment fail

Tech Guide 机器学习 deep learning

October 4, 20260 comment(s)

Introduction to AutoML: How AI Chooses Models and Tunes Hyperparameters Itself

What is AutoMLAutomated Machine Learning (AutoML) aims to automate the parts of the machine learning pipeline that traditionally rely on human experience and repeated trial and error. It lets people w

Tech Guide 机器学习 Automation

October 4, 20260 comment(s)

Introduction to Time Series Forecasting: How AI Predicts the Future

What is time series predictionTime Series Forecasting studies the use of past data arranged in chronological order to predict future values. The difference between it and regular regression is that th

Tech Guide 机器学习 AI

31 post(s)