overfitting | BestHub

DaTaobao Tech

Apr 22, 2024 · Artificial Intelligence

Neural Networks and Deep Learning: Principles and MNIST Example

The article reviews recent generative‑AI breakthroughs such as GPT‑5 and AI software engineers, explains that AI systems are deterministic rather than black boxes, and then teaches neural‑network fundamentals—including activation functions, back‑propagation, and a hands‑on MNIST digit‑recognition example with discussion of overfitting and regularization.

Deep LearningMNISTactivation functions

0 likes · 17 min read

Neural Networks and Deep Learning: Principles and MNIST Example

Alimama Tech

Oct 19, 2022 · Artificial Intelligence

Understanding the One-Epoch Overfitting Phenomenon in Deep Click-Through Rate Models

The study reveals that industrial deep click‑through‑rate models often overfit dramatically after the first training epoch—a “one‑epoch phenomenon” caused by the embedding‑plus‑MLP architecture, fast optimizers, and highly sparse features, with performance dropping sharply unless sparsity is reduced or training is limited to a single pass.

MLPctrdeep learning

0 likes · 15 min read

Understanding the One-Epoch Overfitting Phenomenon in Deep Click-Through Rate Models

Model Perspective

Jul 30, 2022 · Artificial Intelligence

How Decision Trees Predict House Locations: From Intuition to Overfitting

This article explains machine learning fundamentals using a house‑location classification example, illustrating how decision trees create split points from features like elevation and price, grow recursively, achieve high training accuracy, and reveal overfitting when evaluated on unseen test data.

Data Visualizationartificial intelligenceclassification

0 likes · 11 min read

How Decision Trees Predict House Locations: From Intuition to Overfitting

DataFunTalk

Sep 3, 2019 · Big Data

The Value of Big Data in Machine Learning: Detailed Illustration and Insights

This article explains how big data enhances machine learning by enabling finer-grained data characterization, improving confidence in statistical conclusions, and supporting smarter learning through multiple stages of model development, illustrated with concrete examples and a discussion of sample size dilemmas.

big datadata analysisfeature engineering

0 likes · 10 min read

The Value of Big Data in Machine Learning: Detailed Illustration and Insights

Tencent Cloud Developer

Mar 19, 2018 · Artificial Intelligence

Basic Concepts of Decision Trees

Decision trees are tree-structured classifiers that split data using attributes chosen for maximal purity measured by Gini impurity or entropy, with algorithms like ID3 selecting splits by information gain, while overfitting is mitigated through constraints and pruning techniques such as REP, PEP, and CCP.

AlgorithmGini ImpurityID3

0 likes · 13 min read

Architects Research Society

Nov 21, 2016 · Artificial Intelligence

Data Science Q&A: Overfitting, Experimental Design, Tall/Wide Data, Chart Junk, Outliers, Extreme Value Theory, Recommendation Engines, and Visualization

This article presents a series of data‑science questions and expert answers covering overfitting, experimental design for user behavior, the distinction between tall and wide data, detecting chart junk, outlier detection methods, extreme‑value theory for rare events, recommendation‑engine fundamentals, and techniques for visualizing high‑dimensional data.

Experimental designRecommendation systemschart junk

0 likes · 18 min read

Data Science Q&A: Overfitting, Experimental Design, Tall/Wide Data, Chart Junk, Outliers, Extreme Value Theory, Recommendation Engines, and Visualization