Deep Learning with PyTorch - Zero to GANs
This course provides an introduction to deep learning using PyTorch, from the basics to advanced models such as Generative Adverserial Networks and Image Captioning. Participants will gain a comprehensive understanding of the PyTorch framework. ▼
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Course Feature
Cost:
Free
Provider:
Udemy
Certificate:
No Information
Language:
English
Start Date:
On-Demand
Course Overview
❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [March 06th, 2023]
What skills and knowledge will you acquire during this course?
This course will provide learners with the skills and knowledge to build deep learning models with PyTorch. Learners will gain an understanding of the basics of PyTorch, such as Tensors and Gradients, as well as more advanced topics such as Linear Regression, Gradient Descent, Logistic Regression, Feedforward Neural Networks, and Training on GPUs. Additionally, learners will be able to explore more advanced topics such as Convolutional Neural Networks, Recurrent Neural Networks, Transfer Learning, and Generative Adversarial Networks.
How does this course contribute to professional growth?
This course provides a comprehensive introduction to deep learning using PyTorch, from the basics to advanced topics such as Generative Adverserial Networks and Image Captioning. It covers topics such as Tensors & Gradients, Linear Regression & Gradient Descent, Classification using Logistic Regression, and Feedforward Neural Networks & Training on GPUs. By taking this course, professionals can gain a better understanding of deep learning and its applications, as well as the skills to build and train deep learning models with PyTorch.
Is this course suitable for preparing further education?
This course is suitable for preparing further education in deep learning with PyTorch. It covers the basics of PyTorch, such as Tensors & Gradients, Linear Regression & Gradient Descent, and Classification using Logistic Regression, as well as more advanced topics such as Feedforward Neural Networks & Training on GPUs. Additionally, the course is updated on a weekly basis with new material, including CNNs, RNNs, transfer learning, and GANs.
Pros & Cons
Boosted enthusiasm for deep learning
Comprehensive explanation of PyTorch
Easy to follow and concise
Good for beginners
Misleading title
Not detailed enough in practical examples
Requires prior knowledge of Python
Course Provider
Provider Udemy's Stats at AZClass
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