대학원 안가고 딥러닝 공부할래요 - Basis for deep learning

Having started immediately upon release and used it for 14 days, the result is Claude Code! (AI Coding), which can be applied immediately by both job seekers and those currently working! I will now tell you the reason why I recommend it to everyone.

To keep up with recent deep learning trends, we examine the context of its breakthrough progress.

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This is a lecture on implementing various artificial neural networks using Pytorch, a deep learning framework that is widely used in the field of artificial intelligence.

To keep up with recent deep learning trends, we examine the context of its breakthrough progress.

Covers linear algebra, which is essential for machine learning/deep learning research.

Build your own powerful stock analysis model that predicts not only the S&P 500 and QQQ ETFs, but also individual stocks, by using AI to analyze over 40 economic indicators and stock price data!

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.

Create AI data analysis and modeling results into a web program.

Learn about job analysis related to Data Science (DS) and Artificial Intelligence (AI) and the learning and employment roadmap for building a career in related jobs.

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

We will learn the core technologies of the 4th industrial revolution, such as ICBM (IoT, Cloud, Big Data, ML) and related technologies such as self-driving cars and metaverse, from the basics to develop the ability to prepare for future technological changes.

Ace the Big Data Analysis Engineer certification, a must-have credential that's far from easy to self-study, in a short amount of time by mastering the data analysis tool R, known for its ease of use!

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 analyze and visualize data and learn machine learning concepts using Orange 3!

Learn machine learning concepts, artificial intelligence learning principles, and mathematical principles for model implementation to fully utilize deep learning!

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The "Pytorch Projects Explained in One Code" edition implements practical deep learning projects using image, video, and natural language data. It focuses on code-centered learning rather than theory, to understand the structure and flow of models.

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.