Welcome to the official website of 2020 2nd International Conference on Applied Machine Learning and Data Science (ICAMLDS 2020). The conference will be held on 21-23 August, 2020 in Chengdu, China with support from by Chengdu University of Technology and Xijing University.
The purpose of the 2020 2nd International Conference on Applied Machine Learning and Data Science is to bring together researchers, engineers and practitioners interested on databases, big data, data mining, applied machine learning, and other aspects of information systems and technology involving advanced applications of artificial intelligence and data.
Contributions describing machine learning techniques applied to real-world problems and interdisciplinary research involving machine learning, in fields like medicine, healthcare, biology, industry, manufacturing, security, education, virtual environments, games, are especially encouraged.
presentation or poster:

Session 1 Artificial Intelligence
Algorithmic, experimental, prototyping and implementation
Big Data Algorithms, Applications and Services
Biometric Identification
Biocomputing and Bioinformatics
Computational Intelligence
Cognitive Processing
Computer Vision
Deep learning
Document Recognition and Understanding
Humanoid Robot
Space Robot
Chatbots
Intelligent Information Processing
Intelligent Modeling and Control Theory
Intelligent Vehicle
Intelligent Video Surveillance
Mass Information Processing
Multimedia Information Processing
Nature Language Processing
Nonlinear System
Pattern Recognition
Quantum Computation and Quantum Information
Speech and Character Recognition
Signal Processing
Unmanned Aircraft
Word Recognition

Session 2 Applications of Machine Learning
Machine learning in medicine and healthcare
Machine learning in bioinformatics and systems biology
Machine learning in industrial and engineering applications
Machine learning in security applications
Machine learning in smart cities
Machine learning in game playing and problem solving
Machine learning in intelligent virtual environments
Machine learning in economics, business and forecasting applications, etc.

Session 3 Data Sciences
Algorithms
Big Data & Analytics
Data integration
Distributed architecture
Automating machine learning
Data visualization
Dashboards and bi
Data engineering
Deployment in production mode
Automated, data-driven decisions