Understanding the concept of deep learning leading to practical artificial intelligence
This course provides essential knowledge needed to understand the structure and operating principles of various artificial neural networks and create good models.
Knowledge of mathematics/data analysis , extensive experience in deep learning/machine learningBased 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'sspecialized knowledgeandresearch 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!! 👇
Recommended for these people
Who is this course right for?
Anyone interested in deep learning
Anyone interested in universities/graduate schools related to artificial intelligence
Need to know before starting?
Passion to do
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안녕하세요.
딥러닝/머신러닝 관련 유튜브를 운영하는 딥러닝 호형입니다.
수학/데이터 분석을 전공하고 다수의 딥러닝 프로젝트를 완료하고 수행하고 있습니다.
머신러닝, 고급 머신러닝, 딥러닝, 최적화 이론, 강화 학습 등의 인공지능내용과 선형 대수학, 미적분, 확률과 통계, 해석학, 수치해석 등의 수학 내용까지 여러분들과 공유할 수 있는 지식을 가지고 있습니다.
모두 만나서 반갑습니다!
* 관련 이력
현) SCI(E) 논문, 국제 학회 발표 다수
현) 인공지능 관련 대학교 자문 다수
전) K기업 전임 연구원 - 데이터 분석 및 시뮬레이션: 신제품 개발, 성능 향상, 신기술 적용
This is a great lecture where you can learn everything from the very basic concepts of deep learning to advanced concepts. And the latter part contains content that is a little bit separate from the concepts, so I think it will be helpful. If you are interested in deep learning but don't know what to study, I think it will be a good starting point. It was good that I was able to ask a lot of questions about things I didn't know because it answered my questions and concerns well.
Thank you for the great review!! And I think it will be helpful to others as well since you asked great questions! I hope you do great research in the future😀
Thank you for your good evaluation. I hope you do well in your future studies! If you have any questions about the lecture content, please leave them anytime!! 😀
Thank you so much for your great review. I really hope it helps you. I hope you continue to grow! If you have any questions, please feel free to ask :)