Data Science

Accelerating Development of New Quality Productivity Empowered by AI Models

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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

Decoding The Smart Learning Machines Closest To The Human Brain

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Decoding The Smart Learning Machines Closest To The Human Brain

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

Top 10 Algorithms in Artificial Intelligence

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Top 10 Algorithms in Artificial Intelligence

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

Comprehensive Summary of Machine Learning Concepts

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Comprehensive Summary of Machine Learning Concepts

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

Comprehensive Summary of Machine Learning Basics

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Comprehensive Summary of Machine Learning Basics

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

How to Pass the TensorFlow Developer Certification Exam

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How to Pass the TensorFlow Developer Certification Exam

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

Top Ten Basic Operations of TensorFlow

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Top Ten Basic Operations of TensorFlow

Click on the above “Beginner Learning Vision“, choose to add “Starred” or “Pinned“ Heavy content delivered first-hand TensorFlow is an open-source, Python-based machine learning framework developed by Google. It provides interfaces in multiple programming languages such as Python, C/C++, Java, Go, and R, and has rich applications in scenarios such as image classification, audio processing, … Read more

Understanding the Decision Process of XGBoost Machine Learning Model

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Understanding the Decision Process of XGBoost Machine Learning Model

Source: Basics and Advanced of Deep Learning This article is approximately 2800 words long and is suggested to be read in 9 minutes. This article visually demonstrates the prediction process of the XGBoost machine learning model to help you better understand it. The algorithm using XGBoost often achieves good results in Kaggle and other data … Read more

XGBoost Hyperparameter Tuning Guide

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XGBoost Hyperparameter Tuning Guide

This article will explain in detail the introduction, functionality, and value ranges of the ten most commonly used hyperparameters in XGBoost, and how to use Optuna for hyperparameter tuning. For XGBoost, the default hyperparameters work fine, but if you want to achieve the best performance, you need to adjust some hyperparameters to match your data. … Read more

Understanding Deep Learning: A Comprehensive Guide

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Understanding Deep Learning: A Comprehensive Guide

Figure1. Deep Learning Mind Map Introduction The concept of deep learning can be traced back to the field of cybernetics between 1940 and 1960. It later developed into connectionism during the 1980s and 1990s, with the third wave of development beginning in 2006 with the expansion of artificial neural networks, evolving into the highly popular … Read more