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A makerspace is a collaborative work space inside a school, library or separate public/private facility for making, learning, exploring and sharing that uses high tech to no tech tools. These spaces are open to kids, adults, and entrepreneurs and have a variety of maker equipment including 3D printers, laser cutters, cnc machines, soldering irons and even sewing machines.
- Keywords:
- Makerspaces Makerspaces in libraries
- Resource Type:
- Others
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Video
Psychology, Computer Science and Neuroscience have a history of shared questions and inter-related advances. Recently, new technology has enabled those fields to move from “toy” small-scale approaches to the study of language learning from raw sensory input and to do so at a large scale that constitutes daily life. The three primary goals of my research are 1) to quantify the statistical regularities in the real world, 2) to examine the underlying computational mechanisms operated on the statistical data, and 3) to apply the findings from basic science to real-world applications. In this talk, I will present several projects in my research lab to show that the advances in human learning and machine learning fields place us at the tipping point for powerful and consequential new insights into mechanisms of (and algorithms for) learning.
Event Date: 28/06/2023
Speaker: Prof. Chen YU (University of Texas at Austin)
Hosted by: Faculty of Humanities
- Subjects:
- Language and Languages
- Keywords:
- Computational linguistics Language acquisition Machine learning
- Resource Type:
- Video
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Video
EDC is organising a series of Sharing Sessions that present departmental project deliverables and innovations in Technology Enhanced Learning, promoting sustainable and impactful practices that resonate across PolyU and beyond, and funded by PolyU’s Quality Incentive Scheme on Online Teaching, Stage I.
This session proudly presents four departments:
EE: VR, AR & machine learning by Dr Fung Yu-fai
LIB: Using DataCamp to Support Online Learning and Teaching of Data Literacy by Mr Ernest Lam
LMS: Gamification and simulation-based teaching by Dr Anthony Pang
SLLO & COMP: Metaverse and virtual learning platforms by Dr Grace Ngai
Event Date: 15/2/2023
Presenter(s): Dr Yu-fai Fung (EE), Mr Ernest Lam (LIB), Dr Anthony Pang (LMS), Dr Grace Ngai (SLLO)
Facilitator(s): Mr Roy Kam (EDC)
- Subjects:
- Lesson Design and Good Practices
- Keywords:
- College teaching Web-based instruction Internet in education Lesson planning Educational technology
- Resource Type:
- Video
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Courseware
This course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.
- Course related:
- COMP1001 Problem Solving Methodology in Information Technology, COMP3011 Design and Analysis of Algorithms, COMP2011 Data Structures, and COMP4434 Artificial Intelligence
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Computer programming Computer science Artificial intelligence Python (Computer program language)
- Resource Type:
- Courseware
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MOOC
The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.
This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.
This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012.
It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start.
- Course related:
- AAE5103 Artificial Intelligence in Aviation Industry
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Artificial intelligence Machine learning
- Resource Type:
- MOOC
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Video
This channel walks you through the entire process of learning to code in Python; all the way from basics to advanced machine learning and deep learning. The primary emphasis will be on image processing and other relevant functionality. Why did I create this channel? To help you (students and researchers) gain a new skill and succeed in your respective fields.
You may think coding is hard and that it's not your cup of tea, but Python made it easy to code even advanced algorithms. In addition, coding will make you self sufficient, it will teach you how to think, it improves your collaborative skills and it can take your career to new heights. Therefore, if you want to stay ahead of your peers and relevant in your field, overcome your fears and start coding!
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Python (Computer program language) Computer programming Computer science
- Resource Type:
- Video
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Video
Machine learning can deliver unprecedented performance. Its application domain has expanded into safety-critical cyber-physical systems such as UAVs and self-driver cars. However, the safety assurance of vehicular control has two conditions: 1) an analytical model of system behaviors such as provable stability, and 2) the software safety certification process (e.g., DO 178C) requires that the software be simple enough so that software safety can be validated by a combination of model checking and near exhaustive testing. Although ML software, as is, does not meet these two safety requirements, the real-time physics model supervised ML architecture holds the promise to 1) meet the two safety requirements and 2) enable ML software to safely improve control performance and safely learn from its experience in real-time. This talk will review the structure of the proposed architecture and some methods to embed physics into ML-enabled CPS control.
Event Date: 12/05/2022
Speaker: Prof. Lui Sha (University of Illinois Urbana-Champaign)
Hosted by: Graduate School
- Subjects:
- Computing, Data Science and Artificial Intelligence and Aeronautical and Aviation Engineering
- Keywords:
- Machine learning Computer software -- Reliability Drone aircraft Vehicles Remotely piloted
- Resource Type:
- Video
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Others
I am fortunate to be among the very first NTU EECS professors to offer two Mandarin-teaching MOOCs (massive open online courses) on NTU@Coursera. The two MOOCs are Machine Learning Foundations (Mathematical, Algorithmic) and Machine Learning Techniques and are based on the textbook Learning from Data: A Short Course that I co-authored. The book is consistently among the best sellers in Machine Learning on Amazon.
The slides of the MOOCs below are available as is with no explicit or implied warranties. The slides themselves are shared by CC-BY-NC 3.0, but the copyright of all materials (figures in particular) remain with the original copyright holder (in almost all cases the authors of the Learning from Data: A Short Course book).
- Course related:
- COMP4432 Machine Learning
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Machine learning
- Resource Type:
- Others
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Video
In 20 episodes, Jabril will teach you about Artificial Intelligence and Machine Learning! This course is based on a university-level curriculum. By the end of the course, you will be able to: * Define, differentiate, and provide examples of Artificial Intelligence and three types of Machine Learning: supervised, unsupervised, and reinforcement * Understand how different AI and ML approaches can be combined to create compelling applications such as natural language processing, robotics, recommender systems, and web search * Implement several types of AI to classify images, generate text from examples, play video games, and recommend content based on past preferences * Understand the causes of algorithmic bias and audit datasets for several of these causes
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Artificial intelligence Human-Computer Interaction Machine learning
- Resource Type:
- Video
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MOOC
Learn the core ideas in machine learning, and build your first models.
- Course related:
- ENG2002 Computer Programming
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Machine learning
- Resource Type:
- MOOC
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