intermediateFree
Deep Learning
by Andrew Ng & Kian Katanforoosh · Stanford Online
4.8(2,200 reviews)
150K+ enrolled10 weeksUpdated 2024-04
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 CNNs
Apply CNNs techniques to solve real-world problems
Understand the fundamentals and key concepts of sequence models
Apply sequence models techniques to solve real-world problems
About This Course
Stanford's deep learning course covering CNNs, RNNs, LSTM, Adam, dropout, BatchNorm, and structuring ML projects.
Curriculum
Module 1: Deep learning & CNNs6 lessons
- Introduction to deep learning
- Deep learning in Practice
- Hands-on Exercise: Deep learning
- Introduction to CNNs
- CNNs in Practice
- Hands-on Exercise: CNNs
Module 2: Sequence models & Hyperparameter tuning6 lessons
- Introduction to sequence models
- Sequence models in Practice
- Hands-on Exercise: Sequence models
- Introduction to hyperparameter tuning
- Hyperparameter tuning in Practice
- Hands-on Exercise: Hyperparameter tuning
Module 3: ML strategy3 lessons
- Introduction to ML strategy
- ML strategy in Practice
- Hands-on Exercise: ML strategy
Instructor
Andrew Ng & Kian Katanforoosh
Instructor at Stanford Online
Pros & Cons
Pros
- Highly rated by students
- Completely free to access
- High-quality video lectures
- Taught by Andrew Ng & Kian Katanforoosh
Cons
- No certificate provided
- Self-paced requires discipline
Free
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