Embark on a comprehensive 10-hour course that demystifies deep learning and neural networks using PyTorch and Python. Learn to build various deep learning models, starting from PyTorch basics and linear regression, progressing through image classification with logistic regression and convolutional neural networks, and culminating in advanced topics like residual networks, data augmentation, regularization, and generative adversarial networks (GANs). Gain hands-on experience by working with provided code examples, covering everything from fundamental PyTorch operations to training complex models on GPUs. Perfect for beginners looking to grasp the essentials of deep learning while developing practical skills in implementing and training neural networks using PyTorch.
Overview
Syllabus
Introduction.
PyTorch Basics & Linear Regression.
Image Classification with Logistic Regression.
Training Deep Neural Networks on a GPU with PyTorch.
Image Classification using Convolutional Neural Networks.
Residual Networks, Data Augmentation and Regularization.
Training Generative Adverserial Networks (GANs).
Taught by
freeCodeCamp.org
