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Deep Learning
by Yann LeCun & Alfredo Canziani · NYU
4.8(1,400 reviews)
100K+ enrolled14 weeksUpdated 2024-02
What You'll Learn
Understand the fundamentals and key concepts of deep learning
Apply deep learning techniques to solve real-world problems
Understand the fundamentals and key concepts of energy-based models
Apply energy-based models techniques to solve real-world problems
Understand the fundamentals and key concepts of graph neural networks
Apply graph neural networks techniques to solve real-world problems
About This Course
NYU's graduate-level deep learning course covering energy-based models, self-supervised learning, and graph neural networks.
Curriculum
Module 1: Deep learning3 lessons
- Introduction to deep learning
- Deep learning in Practice
- Hands-on Exercise: Deep learning
Module 2: Energy-based models3 lessons
- Introduction to energy-based models
- Energy-based models in Practice
- Hands-on Exercise: Energy-based models
Module 3: Graph neural networks3 lessons
- Introduction to graph neural networks
- Graph neural networks in Practice
- Hands-on Exercise: Graph neural networks
Module 4: Self-supervised learning3 lessons
- Introduction to self-supervised learning
- Self-supervised learning in Practice
- Hands-on Exercise: Self-supervised learning
Instructor
Yann LeCun & Alfredo Canziani
Instructor at NYU
Pros & Cons
Pros
- Highly rated by students
- Completely free to access
- High-quality video lectures
- Taught by Yann LeCun & Alfredo Canziani
Cons
- No certificate provided
- Requires significant prior knowledge
- Self-paced requires discipline
Free
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