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AI Core Technologies

  • Leading research in AI, machine learning, computer vision, data mining, NLP, neural networks, optimization, deep learning and more
  • Insights from famous AI experts
  • Live webinar (recording)

Insights from our Authors and Editors

Lin Zhouchen	 © Springer

Prof. Zhouchen Lin

Accelerated Optimization in Machine Learning: First-Order Algorithms

Liu Zhiyuan	 © Springer

Prof. Zhiyuan Liu  

Representation Learning for Natural Language Processing

Yi Pan © Springer

 Prof. Yi Pan

Artificial Intelligence in Medical Images – Opportunities and Challenges

Jie Tian	 © Springer

Prof. Jie Tian

Artificial Intelligence Based New Era of Optical Molecular Imaging

Featured Books

Selected chapters are free to read until 15 August, 2020.  Free textbooks in Computer Science, learn more.

Book cover: Evolutionary Learning: Advances in Theories and AlgorithmsEvolutionary Learning: Advances in Theories and Algorithms

Selected chapter | Introduction


Book cover: Monte Carlo MethodsMonte Carlo Methods

Selected chapter | Introduction to Monte Carlo Methods


Book cover: A Matrix Algebra Approach to Artificial IntelligenceA Matrix Algebra Approach to Artificial Intelligence

Selected  chapter | Basic Matrix Computation


Book cover: Accelerated Optimization for Machine LearningAccelerated Optimization for Machine Learning 

Selected  chapter | Accelerated Algorithms for Constrained Convex Optimization


Book cover: Deep Reinforcement LearningDeep Reinforcement Learning

Selected  chapter | Introduction to Reinforcement Learning


Book cover: Representation Learning for Natural Language ProcessingRepresentation Learning for Natural Language Processing

Open Access |  Click to access the title


Book cover: Introduction to Deep LearningIntroduction to Deep Learning

Selected  chapter | Machine Learning Basics


Book cover: Applied Machine LearningApplied Machine Learning

Selected  chapter | Learning to Classify


Book cover: Linear Algebra and Optimization for Machine LearningLinear Algebra and Optimization for Machine Learning

Selected  chapter | Optimization Basics: A Machine Learning View


Book cover: Broad Learning Through FusionsBroad Learning Through Fusions

Selected  chapter | Broad Learning Introduction


Book cover: Explainable AI: Interpreting, Explaining and Visualizing Deep LearningExplainable AI: Interpreting, Explaining and Visualizing Deep Learning

Selected  chapter | Towards Explainable Artificial Intelligence


Book cover: Automated Machine LearningAutomated Machine Learning: Methods, Systems, Challenges

Selected  chapter | Hyperparameter Optimization


Selected chapters from featured proceedings

Read more featured book chapters

Live Webinar

人工智能核心技术研讨会   

  • 林宙辰,北京大学信息科学技术学院教授,IAPR/IEEE Fellow     演讲主题机器学习中优化算法前沿简介
  • 陶建华,中国科学院自动化研究所研究员,模式识别国家重点实验室副主任    演讲主题情感识别技术现状与挑战
  • 刘知远,清华大学计算机系副教授,中文信息学会青年工作委员会执委、副主任    演讲主题知识指导的自然语言处理

点击观看直播回放!

Live Webinar: AI Core Technologies   

Presenters: 

  • Prof. Lin Zhouchen, Key Laboratory of Machine Perception (Ministry of Education), School of EECS, Peking University
  • Prof. Tao Jianhua, Institute of Automation, Chinese Academy of Sciences (CASIA), Deputy Director,  National Laboratory of Pattern Recognition (NLPR)
  • Prof. Liu Zhiyuan, Department of Computer Science and Technology at Tsinghua University

Click to watch the recording of the webinar!

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