핸즈온 머신러닝 2

This is a course covering the GitHub notebooks and bonus content from <Build a Large Language Model from Scratch> (Gilbut, 2025). GitHub: https://github.com/rickiepark/llm-from-scratch/ <Build a Large Language Model from Scratch> is the Korean translation of the bestseller <Build a Large Language Model (from Scratch)> (Manning, 2024) by Sebastian Raschka. This book provides a way to learn and utilize the operating principles of large language models by building a complete model starting from scratch with OpenAI's GPT-2 model.

The ultimate machine learning and deep learning tutorial that teaches you like a 1:1 private lesson with Hanbit Media's Honkong series, understand with hundreds of hand drawings, and practice right away with just a browser through Google Colab

Wake up your sleeping coding brain. From Python basics to machine learning, all in one book! This book is an introductory computer science book based on MIT lectures, so even beginners who know nothing about programming can easily read it. Wake up your sleeping coding brain with topics essential for introductory programming, such as computational thinking and simple algorithms. Through brain-boosting problems provided in each chapter, we will look at practical topics such as data visualization, simulation, data calculation techniques, and machine learning.

This lecture guides readers to deep learning with the most appropriate pace and straight direction, one step from concept to formula and one step from coding. In addition, there are over 100 graphs, illustrations, and diagrams, so you can easily and quickly accept abstract concepts. Another unique feature of this lecture is that you can start practicing right away by simply accessing a web browser without installing a program. After comfortably understanding the theory, you can directly code and conquer four representative deep learning problems with your eyes, so it is not lacking as a textbook for deep learning. The concepts or terms that you must go over are reviewed twice in the ‘Wait! Let’s move on to the next’ corner in the middle of the text and the ‘Memory Card’ corner at the end of the chapter to increase the learning effect. Let’s quickly overcome deep learning head-on with ‘Do it! Introduction to Deep Learning.’

We will cover the concept of machine learning in a JavaScript environment. We will cover the form and code of implementing machine learning with JavaScript and TensorFlow.js.

This is a comprehensive machine learning project course that learns various useful machine learning regression and classification projects along with theory using Python and TensorFlow 2 based on Boston Marathon big data.

Through this course, you will learn and use various functions of machine learning agents, such as multi-agents, curriculum learning, and distributed learning. You will also learn about reinforcement learning algorithms that can respond to curiosity-based exploration and variable inputs.

Understand the basic concepts and latest trends of big data, and through technical understanding of big data analysis techniques, extract data patterns to present methods for business application. Through big data, you can create new businesses and develop insights into future business environments.

If you want to be recognized as a machine learning expert based on large-scale data, from understanding the core framework of Spark machine learning, to SQL-based data processing through difficult practical problems, to data analysis through business domain analysis, and to the ability to implement optimized machine learning models, please join this course.

Let's understand the main algorithms of machine learning and deep learning, and learn about artificial intelligence!

AI is not a technology that suddenly appeared. To properly see AI's present and future, you must understand 70 years of challenges and failures. 👉 "The moment you understand AI history, you can see both its principles and future together." Start right now!

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.

From Multi Head Attention to the Original Transformer model, BERT, and Encoder-Decoder based MarianMT translation model, you'll learn Transformer inside and out by implementing them directly with code.

Through this course, students will learn various reinforcement learning theories and implement them themselves, as well as create a reinforcement learning environment to test the reinforcement learning algorithm implemented using Unity Machine Learning Agents.

Make your own AI autonomous vehicle! This is a course where you can learn about AI and reinforcement learning in the most fun and fastest way. This course was produced by the developer ranked #1 in DeepRacer Korea.

AI is not just a simple technology, but was born from people's questions and the flow of the times. Understanding this flow allows you to connect with any new technology without fear. 👉 "The moment you learn AI's roots through stories, you'll see the context." Start now!

This course starts with the question "If I had been on the Titanic, could I have survived?" and completes a full-stack project that develops an AI model to predict survival probability based on actual data and serves it as a web service. You'll practice the entire process of AI and web development, from deep learning modeling using PyTorch, building a backend server with FastAPI, to implementing a user interface with Next.js.

The PyTorch_Project Edition, understood instantly with code, implements practical deep learning projects using image, video, and NLP data, understanding model structure and flow through code-centric learning over theory.

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!

ChatGPT and generative AI have deeply penetrated into our work and daily lives. From deepfakes, hacking, copyright infringement, Naver Whale Bot, to ethics in digital workplaces... The changes AI brings are not just technological issues. Right now, at this very moment, ethical issues are already occurring within the AI you're using. This course focuses on learning about the ethical issues that have exploded with the emergence of generative AI through real-world case studies.

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)

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.

The automotive and parts manufacturing industry is a field where innovation is essential amid fierce global competition and complex supply chains. This course focuses on how AI technology can be applied in the field, explaining actual cases including production efficiency improvement, quality inspection automation, equipment predictive maintenance, and supply chain optimization. From the foundational understanding needed for AI implementation to strategies and risk management considerations for field application, this course covers topics step by step, providing knowledge and insights that practitioners and managers can immediately utilize.

You can create a deep learning analysis environment in the cloud using Docker. When Docker images managed by Google, MS, etc. are combined with the cloud, you can work with the latest deep learning analysis methods on your computer.