Shin Kyung-sik's Deep Learning Odyssey - Convolutional Layers and Pooling Layers

This lecture focuses on convolution, the most important operation in computer vision using deep learning.

Build a solid theoretical foundation of images essential before learning deep learning-based computer vision. Understand the essence of image data, such as pixels, resolution, and color representation, and cultivate practical programming skills to read, transform, and preprocess images using Python.

This is a lecture that provides a brief introduction to the field of computer vision.

This is a lecture that condenses the mathematics curriculum taught in middle and high school. You will learn the necessary mathematical knowledge and techniques through extensive practice for each item.

This is a lecture on data visualization using the Matplotlib library.

This is a course where you learn the basic calculus and PyTorch's Autograd functionality needed to get started with deep learning.

Learn virtual environment concepts and setup methods.

This is a lecture on implementing practical code using PyTorch features based on the code directly implemented in Gradient-based Linear Regression (1). Additionally, it's a lecture where you'll theoretically learn about the necessity of data preprocessing, its theory, and its impact on learning, and implement it with practical code.

This is a lecture for perfectly understanding the process of training the simplest form of deep learning model using gradient descent.

This is a course that intensively covers gradient descent, the most fundamental learning algorithm in deep learning.

This is a lecture on how to use NumPy and practice its application in real-world scenarios.

This is the fifth lecture in the [인공지능을 위한 파이썬] series. It is a course that provides practical exercises used in Machine Learning and Deep Learning, along with Python grammar.

[Python for AI] This is the fourth lecture in the series. It is a lecture that covers Python grammar along with practical exercises used in machine learning and deep learning.

[Python for AI] Third lecture in the series. Learn how to debug Python code.

This is the second lecture in the [Python for AI] series. It's a lecture that provides practical exercises used in machine learning and deep learning, alongside Python grammar.

This is a course that offers extensive practice in Python's basic syntax. This is a course that provides practical exercises used in Machine Learning and Deep Learning, along with Python's syntax.

This is the first lecture in linear algebra, and it is a lecture that geometrically understands vectors and vector operations.

Limits of functions, derivatives, differentiation rules, derivative formulas, applications of differentiation

This course teaches you how to use LaTeX to write formulas.

This lecture focuses on convolution, the most important operation in computer vision using deep learning.

Build a solid theoretical foundation of images essential before learning deep learning-based computer vision. Understand the essence of image data, such as pixels, resolution, and color representation, and cultivate practical programming skills to read, transform, and preprocess images using Python.

This lecture is for those who have heard of the term deep learning but don't know where to start :)

This is the fifth lecture in the [인공지능을 위한 파이썬] series. It is a course that provides practical exercises used in Machine Learning and Deep Learning, along with Python grammar.

This course is a fun project that learns theories and processes images and videos with OpenCV (Open Source Computer Vision Library) and uses deep learning modules (dnn, Deep Neural Network) to identify and recognize faces, eyes, and various objects.

If you want to properly learn OCR technology that's truly used in practice, this one course is all you need! Aiming for over 98% accuracy even with unstructured documents and complex layouts, based on the latest SOTA models and real-world know-how, we build enterprise-level OCR projects together.

This course allows you to build an AI portfolio by cloning the Amenity Detection project from the Airbnb Data Science team—a prime example of TensorFlow utilization—and documenting the entire process on a GitHub blog.

This is an all-in-one course where you can learn the entire process from the basics of deep learning, TensorFlow, and computer vision to practical applications through a real-world license plate recognition project. Through various hands-on exercises, you can develop the practical skills to apply the latest deep learning models to custom datasets.

Analyze over 40 types of economic indicators and stock data with AI to create your own powerful stock price analysis model that predicts not only S&P 500 and QQQ ETF, but also individual stocks!

Building a Full-Stack System Without Coding: Complete the entire pipeline from data collection to AI/ML analysis and web dashboards using only Korean prompts (Vibe Coding). Owning a 100% Automated Pipeline: Secure an independent stock analysis tool that sends S&P 500 screening and investment opinions via Telegram every morning. Acquiring a Practical Data-Based Investment Framework: Master institutional-level data analysis and risk management capabilities based on source code currently in actual operation.

Still lost on CNN even after studying it? I'll concisely explain CNN's core mechanics.

I recommend this to those who want to possess their own technical skills and those who want to learn web development step-by-step. We teach everything starting from the history of web browsers and languages.

AI Artificial Intelligence, it goes without saying that mobile is the trend. But how do you learn machine learning and deep learning and use them on mobile? Now, let's learn useful mobile Computer Vision projects that are used in daily life.

This course is an introductory program designed so that learners who are new to AI technology can easily understand and follow along. Through the lectures, you will learn the basic concepts and usage methods of AI platforms, and conduct hands-on practice directly generating images using various AI tools. Upon completing this course, you will become much closer to AI and acquire the capability to create AI images that can visually implement creative ideas.

Essential certification for the AI era, MS AI-900! 🚀 Did you know? ChatGPT operates exclusively on Microsoft Azure! If you want to properly utilize Microsoft Azure OpenAI, which exclusively provides the latest GPT models, now is the perfect opportunity. Grow into an Azure AI services expert through the AI-900 course and master enterprise-grade AI solutions that companies trust. Secure global official certification and enhance your competitiveness as a true AI professional!

This course aims to cover the latest Gemini API SDK (@google/genai) in a Node.js and TypeScript environment. You will learn how to use multimodal technology to process text, images, and video simultaneously. We will practice the entire process, from issuing an API key to project setup and model calling.

Let's create a web app that uploads an image and uses OpenCV to process it and detect faces.

This course covers everything from the basics to hands-on practice of AI platforms, and is a program where you can learn AI image generation technology. Learners can understand the fundamental concepts of AI and develop the ability to generate AI images using various tools and technologies. Through this course, you can enhance your understanding of the AI field and learn how to directly generate AI images in real-world applications.

Solve the point where 80% get stuck at makeathons. Complete Raspberry Pi · Computer Vision · LLM · 3D Design in 4 weeks! Achieve top rankings at makeathons with a demonstrable smart mirror PoC!

AI does the coding, I get the results! Maximize practical programming skills, achievable even for beginners!