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Fundamentals of Deep Learning

Fundamentals of Deep Learning
Dive into the essentials of deep learning, focusing on classification, CNNs, and an introduction to GANs with hands-on activities.

Details

This is an introduction to the essentials of artificial intelligence, specifically tailored for those new to the field or looking to update their skills. This program will cover the core concepts of deep learning, focusing primarily on classification tasks and Convolutional Neural Networks (CNNs), essential for applications in image processing and computer vision. Mentee(s) will also gain insight into Generative Adversarial Networks (GANs), showcasing the creative capabilities of neural networks. Whether you're a student, professional, or enthusiast, this session will equip you with a solid foundation in the basics of deep learning and its practical applications. We will have hands-on exercises preliminary using PyTorch. 

Goal 1

Introduction to the mathematical concepts and formulations.
Estimated Completion Date
9/10/2024

Goal 2

1. Implementation of the first image classification DL model from scratch.
2. Implement and optimize the first image semantic segmentation DL model.
Estimated Completion Date
11/12/2024

Goal 3

Implement the first Generative Adversarial Network (GAN) to generate realistic fake images.
Estimated Completion Date
12/23/2024

Status

In Progress

Mentor

South Dakota State University

Mentee

Pacific Northwest National Laboratory