How Machines Learn: Principles of AI learned for fun

How Machines Learn: Principles of AI learned for fun, available at $54.99, with 15 lectures, and has 1 subscribers.

You will learn about Understanding the fundamental principles and algorithms of machine learning and deep learning Acquiring methods for optimizing model performance through hyperparameter tuning Gaining knowledge of various deep learning architectures (CNN, DNN, etc.) and their structure and operation principles Recognizing and addressing major deep learning issues and challenges This course is ideal for individuals who are This course is designed for anyone interested in learning about machine learning and deep learning principles, regardless of their background or experience level. or It is ideal for beginners, enthusiasts, and professionals who want to gain a solid understanding of AI concepts and applications. The course is also suitable for those who wish to explore the world of AI for personal development or career advancement. It is particularly useful for This course is designed for anyone interested in learning about machine learning and deep learning principles, regardless of their background or experience level. or It is ideal for beginners, enthusiasts, and professionals who want to gain a solid understanding of AI concepts and applications. The course is also suitable for those who wish to explore the world of AI for personal development or career advancement.

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Summary

Title: How Machines Learn: Principles of AI learned for fun

Price: $54.99

Number of Lectures: 15

Number of Published Lectures: 15

Number of Curriculum Items: 15

Number of Published Curriculum Objects: 15

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Understanding the fundamental principles and algorithms of machine learning and deep learning
Acquiring methods for optimizing model performance through hyperparameter tuning
Gaining knowledge of various deep learning architectures (CNN, DNN, etc.) and their structure and operation principles
Recognizing and addressing major deep learning issues and challenges

Who Should Attend

This course is designed for anyone interested in learning about machine learning and deep learning principles, regardless of their background or experience level.
It is ideal for beginners, enthusiasts, and professionals who want to gain a solid understanding of AI concepts and applications. The course is also suitable for those who wish to explore the world of AI for personal development or career advancement.

Target Audiences

This course is designed for anyone interested in learning about machine learning and deep learning principles, regardless of their background or experience level.
It is ideal for beginners, enthusiasts, and professionals who want to gain a solid understanding of AI concepts and applications. The course is also suitable for those who wish to explore the world of AI for personal development or career advancement.

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!

Course Curriculum

Chapter 1: Machine Learning and Deep Learning

Lecture 1: Section Introduction

Lecture 2: Machine Learning Overview

Lecture 3: How Machines Learn

Lecture 4: Hyperparameters

Lecture 5: Deep Learning and DNN

Lecture 6: CNN and DeepRacer Model

Lecture 7: Deep Learning Issues

Chapter 2: Reinforcement Learning (Bounus)

Lecture 1: Section Introduction

Lecture 2: Reinforcement Learning Overview

Lecture 3: Goals in Reinforcement Learning

Lecture 4: Types of Reinforcement Learning Algorithms

Lecture 5: Data Structures in Reinforcement Learning

Lecture 6: Training Models in Reinforcement Learning

Lecture 7: Challenges and Issues in Reinforcement Learning

Lecture 8: Hyperparameters and Terminology in RL

Instructors

AI Castle
artificial intelligence development and education company

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Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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