Building and Training Neural Networks with PyTorch
Master neural network development with PyTorch: from classification to advanced architectures.Building and Training Neural Networks with PyTorch
Master neural network development with PyTorch: from classification to advanced architectures.Building and Training Neural Networks with PyTorch
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full PyTorch Ultimate 2024 - From Basics to Cutting-Edge Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
Instructors:
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What you'll learn
Build and train neural networks using PyTorch framework
Implement CNNs for image and audio classification tasks
Develop object detection models using YOLO algorithm
Apply transfer learning and pre-trained networks effectively
Create RNN and LSTM networks for sequential data processing
Skills you'll gain
This course includes:
5.3 Hours PreRecorded video
4 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 7 modules in this course
This comprehensive course focuses on building and training neural networks using PyTorch. Starting with classification models and confusion matrices, students progress to implementing CNNs for image and audio processing. The curriculum covers advanced topics including object detection with YOLO, neural style transfer, and recurrent neural networks. Through hands-on exercises and practical implementations, learners develop expertise in various neural network architectures while gaining proficiency in PyTorch framework.
Classification Models
Module 1 · 1 Hours to complete
CNN: Image Classification
Module 2 · 1 Hours to complete
CNN: Audio Classification
Module 3 · 48 Minutes to complete
CNN: Object Detection
Module 4 · 1 Hours to complete
Style Transfer
Module 5 · 39 Minutes to complete
Pre-Trained Networks and Transfer Learning
Module 6 · 16 Minutes to complete
Recurrent Neural Networks
Module 7 · 1 Hours to complete
Instructor
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