PyTorch Deep Learning: Computer Vision Fundamentals
Master computer vision with PyTorch. Learn deep neural networks, CNNs, and essential Python data science libraries for image processing.
Master computer vision with PyTorch. Learn deep neural networks, CNNs, and essential Python data science libraries for image processing.
This comprehensive course introduces PyTorch and deep learning for computer vision applications. Starting with PyTorch basics and tensor operations, students progress to building neural networks and CNNs. The curriculum includes hands-on training with the CIFAR10 dataset, implementation of LeNet architecture, and extensive coverage of Python fundamentals. Optional modules cover essential data science libraries including NumPy, Pandas, and Matplotlib. Ideal for beginners in deep learning and computer vision.
Instructors:
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What you'll learn
Master PyTorch fundamentals and tensor operations
Implement gradient descent using AutoGrad
Build and train convolutional neural networks (CNNs)
Develop computer vision applications with LeNet architecture
Create deep learning models for image processing
Utilize GPU acceleration for efficient computation
Skills you'll gain
This course includes:
427 Minutes PreRecorded video
5 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 12 modules in this course
This comprehensive course introduces deep learning and computer vision using PyTorch. The curriculum progresses from fundamental Python programming concepts to advanced deep learning applications. Students learn essential PyTorch operations, AutoGrad functionality, and CNN architectures including LeNet. The course includes optional modules covering Python basics and data science libraries (NumPy, Pandas, Matplotlib), making it accessible to beginners while providing depth for experienced programmers.
Welcome Aboard
Module 1 · 16 Minutes to complete
Introduction to PyTorch and Tensors
Module 2 · 1 Minutes to complete
Diving into PyTorch
Module 3 · 50 Minutes to complete
AutoGrad in PyTorch
Module 4 · 16 Minutes to complete
Creating Deep Neural Networks in PyTorch
Module 5 · 18 Minutes to complete
CNN in PyTorch
Module 6 · 49 Minutes to complete
LeNet Architecture in PyTorch
Module 7 · 24 Minutes to complete
Optional Learning- Python Basics
Module 8 · 2 Hours to complete
Optional Learning - Mini Project with Python Basics
Module 9 · 57 Minutes to complete
Optional Learning - Python for Data Science with NumPy
Module 10 · 50 Minutes to complete
Optional Learning - Python for Data Science with Pandas
Module 11 · 45 Minutes to complete
Optional Learning - Python for Data Science with Matplotlib
Module 12 · 1 Hours to complete
Fee Structure
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Instructor
Enhancing IT Education Through Expert-Led Learning
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