Multi-Task-Learning on JetRacer

This repository provides educational content and projects related to Multi-Task-Learning in various domains, such as self-driving cars. Below is an overview of the modules and lessons covered.

Introduction to Multi-Task-Learning

1. Introduction to Multi-Task Learning
2. Architecture, Encoders & Decoders, Challenges, and Solutions
3. Project: UTK-Face Dataset
4. Implementing Multi-Task Learning
5. 10 Multi-Task Learning Architectures to Know About
6. HydraNets in Computer Vision

Running HydraNet Models for Self-Driving Cars

1. HydraNet for Self-Driving Car Project
2. Building the Encoder
3. Building the Decoder
4. Running the HydraNet
5. 3D Segmentation

Training HydraNet Models for JetRacer

1. Training a HydraNet — Overview
2. Building a DataLoader
3. Assembling the HydraNet
4. Training the Model
5. Introduction to Deep Learning Optimization

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Getting Started

1. Clone the repository:

   git clone https://github.com/CagriCatik/multi-task-learning.git
   cd multi-task-learning

2. Follow the instructions in each module to start learning and building projects with HydraNet and multi-task learning models.

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Documentation

The full documentation for this project is also available as an mdBook. It provides a structured guide with additional information, resources, and interactive content for each module.

To view the documentation, either clone the mdBook and run it locally or access the hosted version via the following link:

• Multi-Task Learning mdBook

You can build and serve the mdBook locally by running:

mdbook build
mdbook serve --open

This will open the book in your web browser for easy navigation through the course materials.