[PyTorch] 実戦人工知能へとつながるディープラーニング - 基礎から論文実装まで

This course provides essential knowledge needed to understand the structure and operating principles of various artificial neural networks and create good models.

Covers essential linear algebra for Machine Learning/Deep Learning research.

This is a lecture that studies Vision Transformer, one of the latest deep learning technologies, and implements a paper using Pytorch. Come experience the new future of the vision field with me!

This is a lecture that studies the physical information neural network, one of the next-generation innovative technologies of deep learning, and implements it directly using Pytorch. Let's learn the next-generation innovative technology of artificial intelligence with me!

This course will teach you from the early YOLO model, a real-time object recognition model, to the latest model. In addition, you will learn various deep learning techniques along with object recognition.

Learn how to understand advanced machine learning models without math and implement them easily in Python.

Learn how to understand advanced machine learning models without math and implement them easily in Python.

This course provides essential knowledge needed to understand the structure and operating principles of various artificial neural networks and create good models.

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.

RAG (Retrieval-Augmented Generation) from theory to the latest multimodal and agent-based RAG! This is a hands-on lecture designed to be understandable even for non-majors. From paper reviews to practical code implementation, it's designed so that even those encountering RAG for the first time can easily follow along.

Time is constantly flowing, and data is constantly accumulating. In this dynamic world, time series data plays a vital role in every aspect of our lives. From the volatility of financial markets to subtle signals of climate change, time series data captures it all. Now learn how to interpret and leverage this powerful data using the power of Python and deep learning!

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 the basics of machine learning & deep learning! Creating and utilizing classification/regression/clustering/artificial neural networks with Python

Let's implement a deep learning framework directly with Excel! Let's solve supervised learning/unsupervised learning/reinforcement learning with the implemented framework!

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.

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.

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 :)

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.

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.

You will create an Android/iOS app based on a simple machine learning model, learn the basics of machine learning, model conversion using TFLite, and the process of implementing an Android app/iOS app.