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Kaggle offers a no-setup, customizable, Jupyter Notebooks environment. Access GPUs at no cost to you and a huge repository of community published data & code. Inside Kaggle you’ll find all the code & data you need to do your data science work. Use over 50,000 public datasets and 400,000 public notebooks to conquer any analysis in no time.
- Subjects:
- Computing
- Keywords:
- Machine learning Artificial intelligence Big data
- Resource Type:
- Others
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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:
- Aeronautical and Aviation Engineering and Computing
- Keywords:
- Machine learning Vehicles Remotely piloted Computer software -- Reliability Drone aircraft
- 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
- Keywords:
- Machine learning
- Resource Type:
- Others
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Video
Welcome to Zero to Hero for Natural Language Processing using TensorFlow! If you’re not an expert on AI or ML, don’t worry -- we’re taking the concepts of NLP and teaching them from first principles with our host Laurence Moroney.
- Subjects:
- Computing
- Keywords:
- Machine learning Natural language processing (Computer science)
- Resource Type:
- Video
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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
- Keywords:
- Human-Computer Interaction Machine learning Artificial intelligence
- 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
- Keywords:
- Machine learning
- Resource Type:
- MOOC
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Video
Gradient Descent is the workhorse behind most of Machine Learning. When you fit a machine learning method to a training dataset, you're probably using Gradient Descent. It can optimize parameters in a wide variety of settings. Since it's so fundamental to Machine Learning, I decided to make a "step-by-step" video that shows you exactly how it works.
- Course related:
- COMP4434 Big Data Analytics
- Subjects:
- Computing
- Keywords:
- Machine learning Computer algorithms
- Resource Type:
- Video
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Video
This video introduces the basic concept and the overall working process of the ANN models, especially how the backpropogation works. How to establish a deep neuro network.
- Course related:
- LGT6801 Guided Study in Logistics I
- Subjects:
- Computing
- Keywords:
- Machine learning Neural networks (Computer science)
- Resource Type:
- Video
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Video
This video is take an adapted version of this course as part of the Stanford Artificial Intelligence Professional Program.
- Course related:
- AP619 Microfabrication Laboratory
- Subjects:
- Computing
- Keywords:
- Machine learning Computer algorithms
- Resource Type:
- Video
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Video
Statistics, Machine Learning and Data Science can sometimes seem like very scary topics, but since each technique is really just a combination of small and simple steps, they are actually quite simple. My goal with StatQuest is to break down the major methodologies into easy to understand pieces. That said, I don't dumb down the material. Instead, I build up your understanding so that you are smarter.
- Course related:
- HTI34016 Introduction to Clinical Research
- Subjects:
- Computing and Mathematics and Statistics
- Keywords:
- Statistics Mathematical analysis Data mining Machine learning
- Resource Type:
- Video
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