Build production-ready deep learning models using PyTorch, with strong foundations, hands-on labs, and real-world engine
Sub Category
- Data Science
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Objectives
- Build deep learning models from scratch using PyTorch with a strong engineering foundation
- Build deep learning models from scratch using PyTorch with a strong engineering foundation
- Understand and apply neural networks, backpropagation, and optimization effectively
- Train, evaluate, and improve models using regularization and generalization techniques
Pre Requisites
- Build CNNs and sequence models for real-world vision and time-series tasks.
- Build CNNs and sequence models for real-world vision and time-series tasks.
- Apply CNNs and sequence models to solve real image and time-series problems end-to-end.
- Create computer vision and time-series solutions using CNNs and sequence networks.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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