Understanding the concept of deep learning leading to practical artificial intelligence

Deep Learning, from the Basics!
Let's learn the core principles of artificial intelligence together.

Why Deep Learning?📝

I am Deep Learning Ho-hyung, who currently runs a YouTube channel about deep learning/machine learning.
( https://www.youtube.com/channel/UCt9jbjxLBawaSaEsGB87D6g/ )

Knowledge of mathematics/data analysis , extensive experience in deep learning/machine learning Based on my project experience and career as a research engineer , I will point out the things you must study.

Lecture Introduction 💡

"This lecture is a theoretical lecture."

Artificial neural networks (ANNs) are a powerful AI technology already being applied in a wide range of fields, including manufacturing, autonomous vehicles, healthcare, biotechnology, and robotics. Indeed, the number of papers submitted is increasing every year, leading to numerous universities worldwide establishing related departments and significant investment from the industry. Similarly, universities in Korea are rapidly establishing AI-related departments . In line with this trend, we've created this course for those seeking a thorough introduction to deep learning .

Deep learning is a subject that requires both conceptual understanding and implementation skills , so many people find it difficult. Therefore, through this lecture, I will try to explain it more easily and highlight the important parts. The curriculum is as follows: The content is organized based on the lecturer's specialized knowledge and research experience, and the lecture is divided into theory and implementation sections.

First, we'll cover essential knowledge about deep learning . Deep learning research often expands or improves on existing concepts. Therefore, understanding the fundamentals and related knowledge is crucial to understanding the latest research. This course will provide an easy-to-understand overview of the fundamentals through examples and diagrams . Second, we'll develop the ability to implement models using PyTorch . The programming part allows you to build various artificial neural networks, such as CNNs, LSTMs, and CAMs, without any separate installation.

Considering your precious time, we've structured this lecture compactly! Shall we begin?

What you will learn in this course ✏️

Are you still simply using other people's code? Or are you implementing it without understanding the concepts? A thorough understanding is essential for application and for identifying existing problems. In this lecture, we'll explain the concepts behind artificial neural networks from the ground up, explaining why they work and demonstrating examples along the way.

Beyond the basics, this course expands on transfer learning , essential for practical research, and covers semi-supervised and unsupervised learning . At the end of the course, we'll provide study tips to help you master deep learning.

Expected Questions Q&A 🙋🏻‍♂️

* This lecture is a theory-based lecture without coding .

Q. Can non-majors also take the course?
A. You can take the course regardless of your major .

Q. What are the benefits of learning deep learning?
A. Deep learning is the most widely utilized machine learning technology, making it a must -learn for anyone entering the field of artificial intelligence. Furthermore, with so many products incorporating deep learning technology already in our lives, acquiring a solid understanding of the technology will be invaluable in AI-related jobs and careers.

Q. Are there any special advantages to this course?
A. Although this is an introductory course, you'll gain knowledge beyond the beginner level, including valuable tips, transfer learning, and model tuning . Furthermore, this course is based on the curriculum of overseas universities and insights gained through actual research .

Go watch the implementation lecture!! 👇