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Artificial intelligence
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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
- Keywords:
- Machine learning Artificial intelligence
- Resource Type:
- MOOC
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Video
What happens when technology knows more about us than we do? Poppy Crum studies how we express emotions -- and she suggests the end of the poker face is near, as new tech makes it easy to see the signals that give away how we're feeling. In a talk and demo, she shows how "empathetic technology" can read physical signals like body temperature and the chemical composition of our breath to inform on our emotional state. For better or for worse. "If we recognize the power of becoming technological empaths, we get this opportunity where technology can help us bridge the emotional and cognitive divide," Crum says.
- Subjects:
- Technology, Electronic and Information Engineering, and Mechnical Engineering
- Keywords:
- Emotion recognition Artificial intelligence
- Resource Type:
- Video
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Video
On the TED@BCG stage, AI pathfinder Philipp Gerbert dispels the myth of AI as a complex and mysterious tool for business. In reality, he says, even those of us outside Silicon Valley can have an intimate understanding of AI and put it to work today. Gerbert walks us through the ABC's of AI and what it can mean for your organization.
- Keywords:
- Business enterprises -- Technological innovations Artificial intelligence
- Resource Type:
- Video
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Video
Here's a paradox: as companies try to streamline their businesses by using artificial intelligence to make critical decisions, they may inadvertently make themselves less efficient. Business technologist Sylvain Duranton advocates for a "Human plus AI" approach -- using AI systems alongside humans, not instead of them -- and shares the specific formula companies can adopt to successfully employ AI while keeping humans in the loop.
- Keywords:
- Business enterprises -- Technological innovations Artificial intelligence
- 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