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Hands-On Deep Learning on PyTorch for Beginners
1,824 students
Hands-On Deep Learning on PyTorch for Beginners
This course is designed for beginners with little no experience in Deep learning or PyTorch.
Created byEmanuel Riquelme
Last updated 7/2023
English
What you'll learn
- Train Convolutional Neural Networks.
- How to apply data transformations using the torchvision library.
- How to efficiently store and load data samples on PyTorch.
- How to leverage GPU acceleration to train neural networks efficiently
- Overall the student will build a solid foundation in the fundamental concepts and techniques required to train neural networks effectively
Explore related topics
Course content
9 sections • 33 lectures • 1h 11m total length
Requirements
- As long as you have a basic understanding of Python, you're all set to dive into the world of Deep learning.
Description
Hands-On Deep Learning with PyTorch: A Beginner's Course:
Whether you're new to neural networks or looking to expand your skills, this course will provide you with a hands-on approach to training neural networks from scratch.
Our comprehensive curriculum covers all the essential components of deep learning, including Neural Networks, Loss Functions, Optimizers, Datasets, and DataLoaders. You'll also learn how to leverage the GPU for accelerated training and gain practical insights into building and training basic neural networks using PyTorch.
What sets this course apart is it's accessibility. You don't need any previous knowledge of neural networks or PyTorch. All you need is a basic understanding of Python, and we'll guide you through the rest.
By the end of the course, you'll have gained the skills to confidently train basic neural networks using PyTorch. Unlock your potential in deep learning and embark on this exciting journey today. Enroll now and start building your expertise in the world of artificial intelligence.
Content of the Course:
Datasets
Data Loaders.
Image Augmentation
Loss Functions
Optimizers.
Activation Functions.
Normalization Techniques.
Convolutional Neural Networks (CNN).
Training Neural Networks.
GPU Acceleration.
Requirements:
The only requirement is basic knowledge of Python.
No experience on Deep learning required.
No experience on PyTorch required.
Who this course is for:
- This course is designed for beginners who are interested in deep learning but lack the theoretical/technical background.
- Beginners that feel overwhelmed with the massive influx of information around and want a streamlined path to build a solid foundation on deep learning.