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15.773 | Spring 2024 | Graduate

# Hands-on Deep Learning

#### Course Description

This is a fast-paced introduction to deep learning with an emphasis on developing a practical understanding of how to build models to solve complex problems involving unstructured data. Topics include the basics of deep neural networks and how to set up and train them, convolutional networks to process images and …
This is a fast-paced introduction to deep learning with an emphasis on developing a practical understanding of how to build models to solve complex problems involving unstructured data. Topics include the basics of deep neural networks and how to set up and train them, convolutional networks to process images and videos, transformers for natural language processing, generative large language models (such as ChatGPT), and text-to-image models (such as Midjourney). Prior familiarity with Python and fundamental machine learning concepts (such as training/validation/testing, overfitting/underfitting, and regularization) is required.

## Course Info

##### Instructor

- Prof. Rama Ramakrishnan

##### Departments

- Sloan School of Management

##### Topics

- Business
  - Information Technology
- Engineering
  - Computer Science

##### Learning Resource Types

theaters Lecture Videos
notes Lecture Notes
assignment Programming Assignments
assignment Problem Sets
Problem Set Solutions
Everyday objects, carefully framed and labeled, illustrate how computer vision models learn to recognize the world. (Image by Max Gruber. License: CC BY. Source: Wikimedia Commons.)

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