Practical Deep Learning with PyTorch
Accelerate your deep learning with PyTorch covering all the fundamentals of deep learning with a python-first framework.
4.01 (1716 reviews)
6 766
students
6.5 hours
content
Oct 2018
last update
$14.99
regular price
What you will learn
Effectively wield PyTorch, a Python-first framework, to build your deep learning projects
Master deep learning concepts and implement them in PyTorch
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Comidoc Review
Our Verdict
Practical Deep Learning with PyTorch offers a thorough exploration of deep learning fundamentals and their implementation in the PyTorch framework. While some code snippets are outdated, overall, it's a well-structured course, especially helpful for beginners seeking an introduction to both deep learning methods and PyTorch. However, there is room for improvement regarding more practical examples and deeper explanations of essential concepts like loss functions, back-propagation, and model validation.
What We Liked
- Comprehensive coverage of deep learning concepts and their implementation in PyTorch
- Well-structured course with a smooth flow between topics, suitable for beginners
- Detailed explanations of networks and diagrams that illustrate relationships
- Valuable as an introductory course to Deep Learning methods and PyTorch framework
Potential Drawbacks
- Some outdated code snippets and installations issues, particularly on Windows
- Lacks in-depth explanations about loss functions, back-propagation algorithm, and basics
- Limited practical examples for certain topics, such as RNNs and LSTMs, with room for improvement
- Insufficient guidance for validating models and addressing overfitting concerns
Related Topics
1259546
udemy ID
19/06/2017
course created date
05/08/2019
course indexed date
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