How Machines Learn: Principles of AI learned for fun

About How Machines Learn: Principles of AI learned for fun

Welcome to the standalone course on "Machine Learning and Deep Learning," a unique offering that has been carefully crafted by referencing a key section of our comprehensive "Exciting AI: Autonomous Driving & RL with AWS DeepRacer" course.

In this specialized course, we will dive deep into the foundations of machine learning and deep learning, both crucial components in the development of autonomous driving technologies. The course is structured as follows:

Machine Learning Overview

How Machines Learn

Hyperparameters

Deep Learning and DNN

CNN Model

Deep Learning Issues

Whether you are a beginner or have some experience in the AI field, this course will provide you with valuable insights into the inner workings of machine learning and deep learning algorithms.

Throughout this course, you'll gain a deeper understanding of how machines learn, the role of hyperparameters, and the differences between deep learning and traditional machine learning.

You'll also explore Deep Neural Networks (DNNs), Convolutional Neural Networks (CNNs), and how they are applied to the DeepRacer Model. Lastly, we will discuss common issues encountered in deep learning and potential solutions.

For your information, this course is designed to provide you with a focused understanding of machine learning and deep learning concepts.

However, if you're curious about not just the theoretical aspects of AI, but also eager to dive into hands-on practice and implementing autonomous driving solutions, we highly recommend enrolling in the full "Exciting AI: Autonomous Driving & RL with AWS DeepRacer" course. By taking the complete course, you'll have the opportunity to explore AI concepts more extensively, and experience the thrill of creating your own autonomous driving models. Don't hesitate to challenge yourself and join us in the exciting world of AI and autonomous driving!