Xu hướng là bắt đầu với Vibe Coding và MCP_Cursor AI
Masocampus
Xu hướng mới nhất của AI tạo sinh, AI Agent! Cách đi trước với Cursor giúp hoàn thành công việc phát triển và MCP mở rộng tính năng!
입문
cursor, mvp, AI Agent
Introduction to Deep Learning
What is deep learning? A course to introduce deep learning and how to use it in practice by completely organizing the concept of deep learning!
What you will learn!
Understanding the learning principles of deep learning, forward propagation and backpropagation
Understanding the concept of deep learning and perceptron
Securing practical application skills through understanding-based deep learning utilization practice
Ability to use Python virtual environments and Keras
Deep learning for the first time, easy for anyone!
Deep Learning: Why Should You Learn It?
What on earth is deep learning?
We wake up in the morning and start our day by asking our smartphone's voice recognition service for the weather. On our way to work, we hear about AI-generated drawings and novels winning awards in competitions. We use a translator to navigate tense conversations with overseas clients at work. At lunchtime, we hear the neighbor bragging about ordering a new car, causing us to feel a pang of distrust in autonomous driving technology.
All of these technologies are made possible by deep learning, and they represent only a small fraction of the changes it has brought about. It's been a decade since the AlphaGo match captivated the world's attention, and in that short time, the world has changed dramatically. The dazzling performance of new big tech companies is also featured in daily economic newspapers.
So what is it about deep learning that has brought about so many changes?
Deep learning can be thought of as the human brain implemented using artificial intelligence technology. Just as stimuli detected by the eyes, nose, mouth, and skin are transmitted to the brain and recognized as signals, digitized information undergoes several stages, allowing the computer to autonomously make judgments and draw conclusions. Of course, as it's a cutting-edge technology, its design requires considerable research and expert knowledge.
However, this isn't the case for general use ! One of Python's greatest strengths—its freely installable modules—has already been developed to implement deep learning, and many people are already using it. The fact that it's available to many means you can also take advantage of it.
That's why Maso Campus offers the "Introduction to Deep Learning" course, which covers the concepts and operating principles of deep learning, making it easy for anyone to get started. For a truly revolutionary boost in productivity, try your hand at deep learning!
Deep learning, so that you can use it properly
We will lay a solid foundation for you.
Deep learning brings about overwhelming productivity improvements regardless of the field!
This is a process of completely understanding the concepts in order to “properly” utilize deep learning.
Essential Components of Deep Learning
Solving the Problems of Deep Learning
Recommended for these people ✅
- Professionals who want to utilize artificial intelligence in their work
- Those who want to build a career in the IT industry (starting a business/changing jobs/joining a company)
- Managers and practitioners who want to introduce AI into their businesses
- Anyone who wants to start deep learning properly from the beginning
You can acquire the following capabilities 👍
- Understanding the concepts of artificial intelligence, machine learning, and deep learning
- Understanding the principles of deep learning components and models
- Understanding deep learning principles and error correction methods
- Ability to build a Python virtual environment and utilize Keras
Unique features of this course!
Thoroughly in 3 steps.
Through this lecture, you will understand the operating principles of the hottest deep learning technology today and be able to implement a deep learning model through practice.
Step 1. Understanding the concept and operating process of deep learning.
We'll delve into what deep learning is, how it differs from machine learning, and why it delivers unparalleled performance ! Once you understand the secrets, utilizing it will become more accurate and easier.
Understanding the Concept of Deep Learning Step 2. Practice the Deep Learning Modeling Process
Representative deep learning algorithms: regression and classification!
You can practice data analysis with models you design yourself and use "real" deep learning.
Understanding Activation Functions Step 3. Bring insights discovered in the digital world to life!
What if we could apply various machine learning techniques based on data and apply the resulting insights to actual work? This could revolutionize decision-making across a wide range of areas, from sales and development to human resources.
Predicting patient survival rates Q&A 💬
Q. Is prior knowledge of Python programming required?
This course and subsequent deep learning courses at Maso Campus require basic Python skills.
For those unfamiliar with Python, we recommend taking Maso Campus' 'Introduction to Python Data Analysis' and 'Practical Python Data Analysis' courses first.
Q. Are there any requirements or conditions for taking the course?
Since this is a hands-on course, we recommend bringing a dual monitor or a spare device that allows you to separate the lecture and practice screens. Furthermore, since the practical training will be conducted on a Windows OS, we recommend taking the course in a Windows environment.
Q. I heard that deep learning requires a high-spec PC. Do I need a high-spec PC for practical training?
While it's recommended to run the course in a high-spec environment, this course will be conducted in a virtual environment utilizing Anaconda and Jupyter Notebook. Therefore, anyone with a standard work PC will be able to complete the course without difficulty.
📢 Please check before taking the class!
- As this is a practice-oriented lecture, it would be helpful to prepare a dual monitor or extra device that can separate the lecture video and practice window.
- Since the training is conducted on a Windows-based basis, we recommend taking the course in a Windows environment.
- Lecture notes and practice files can be downloaded from the "Textbook Download Center" section.
Recommended for
these people
Who is this course right for?
Practitioners who want to try using artificial intelligence in their work
Anyone who wants to build a career in the IT industry, such as starting a business, changing jobs, or joining a company
Managers and practitioners who want to introduce artificial intelligence into their business
Anyone who wants to get off to a good start building their deep learning capabilities
Need to know before starting?
This course requires basic Python skills.
I recommend that you take Maso Campus' [Introduction to Python] and [Python Practice] courses first.
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Reviews
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Rating
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"어제보다 성장하겠습니다. 그리고, 어제보다 성장하려는 사람을 돕겠습니다."
마소캠퍼스의 진심과 소망을 담은 Actionable Content로,
2013년부터 온오프라인으로 함께해 온 누적 강의 1억시간!
이 소중한 경험과 시간은 언제나 마소캠퍼스와 수강생 모두의 성장의 원천입니다.
마소캠퍼스 팀은 우리의 모두의 성장을 위해 두 가지 원칙을 반드시 지킵니다.
1. 배우면 반드시 쓸 수 있는 Actionable Content
2. 참여자의 시간과 수고를 존중하는 Time-Saving Curriculum
마소캠퍼스의 Actionable and Time-Saving Curriculum으로 성장의 길을 함께 걸어나가길 기원합니다.
Curriculum
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38 lectures ∙ (3hr 40min)
Course Materials:
Lecture resources
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1 reviews
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1 reviews
joc12454232Reviews 9
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Average Rating 4.9
4
100% enrolledThời gian chạy ngắn nên tôi đã dành cả cuối tuần để xem hết. Trước hết, nội dung đơn giản hơn tôi mong đợi. Tôi tưởng bạn chỉ giải thích những điểm chính. Tôi cảm thấy thoải mái khi nghe giảng viên vì anh ấy dường như giải thích mọi thứ một cách bình tĩnh hơn khi bài giảng tiến triển. Tôi đã mua nó với giá thông thường, nhưng nếu bạn quan tâm đến khóa học này, bạn có thể muốn mua nó khi nó đang giảm giá.
- masocampusInstructor
Cảm ơn đã lắng nghe! Tôi rất vui khi biết rằng nó đơn giản vì tôi đã cố gắng giải thích những điểm chính càng nhiều càng tốt. Tôi sẽ thưởng cho bạn những bài giảng tốt hơn trong tương lai. Nếu bạn có bất kỳ câu hỏi nào, xin vui lòng hỏi.
$46.20
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