김일한의 인공지능을 위한 텐서플로2 + 케라스 라이브러리 실전 적용

This course covers everything from JSP basics to a car purchasing shopping mall project. After completing the course, you will be able to carry out a real project right away. (This course does not provide Q&A.)

Currently, Android can be developed using the Java and Kotlin languages. The same Android application can be developed using either language. This course covers most of the content from basic to advanced Android application development, and all code is written using the Kotlin language starting from the basic content. We also use Material 3, Google's latest UI library. This course mainly covers menus, Android application components, threads, and Fragments among the entire Android curriculum, and future courses are planned to cover more in-depth topics. Soft Campus will always strive to provide the latest lectures. Thank you.

This course is a Java Android app development course consisting of a total of 4 parts. In the third lecture, we will look at data management and networks in Android apps.

This course is based on the concepts learned in the Spring Framework and teaches how to implement web applications. All the learned content is summarized and a final mini-project is conducted. After completing the course, you will be able to immediately perform a real project. It contains a total of 65 lectures and 29 hours and 37 minutes of study time.

You can learn how to create a clicker game based on Unity.

You can create hybrid casual games using Unity 6.

Learn C# in the Unity environment. Learning C# will help you naturally learn the Unity development environment, which will be very beneficial for beginner developers.

Android 15 Version App Development with Latest Material 3 Library Part 1 UI Programming Course.

With the latest version in 2024 and a running time of 17 hours and 48 minutes, you can completely conquer Kotlin with this one course.

This course teaches you how to develop front-end web using React. You will learn the core JavaScript grammar for React, CDN-based React development, and NPM-based React development methods.

Using Unity based on the C# language, you will learn how to create a defense game step by step.

Develop three practical projects (memo application, LBS application, bulletin board application using FireBase).

You can learn the basic principles of run games like Cookie Run and create Unity games through practical projects in Unity by genre.

This course is a Java Android app development course consisting of a total of 4 parts. In the second lecture, we will look at the menu and the 4 major components through practical examples.

This lecture is a lecture by instructor Jaeseong Yoon, who teaches Android lectures at App School: Like a Cool Lion.

This course is a course to learn the basics of Python Windows programming. It enhances understanding by explaining how to use widgets and providing sample codes.

This course is a course to learn the basics of Python grammar. It enhances understanding by combining grammar explanations with sample code. Learn basic Python libraries.

This course is a course to learn data analysis methods using the Pandas library. You will learn practical application methods by learning the library and analyzing sample data in parallel.

You can understand JSP WEB MVC Model2 Programming and learn how to apply it in practice through the MVC Model2 bulletin board project. (This lecture does not provide Q&A with the instructor.)

You can master mobile UX design practices using Adobe XD. (Study materials and practice files provided)

This is a comprehensive course on Keras theory and practice that uses Keras and Python, the common language of artificial intelligence, to learn various useful machine learning regression, classification, and deep learning neural network projects along with theory.

This lecture covers the contents of the Amazon bestseller <Hands-on Machine Learning 2nd Edition>. Using the representative machine learning library, scikit-learn, you will learn various machine learning algorithms and evaluation methods. Also, using the most famous deep learning libraries, TensorFlow and Keras, you will learn theories and practices from artificial neural networks to reinforcement learning. This lecture is not yet complete. One to two lectures will continue to be added every week.

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!

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 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.

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.

Still managing ML experiments manually? 🤔 Automate everything from experiment tracking to model deployment with MLflow and dramatically boost development productivity! A must-have skill for data scientists and ML engineers 💡 Start now! 🚀

Tensorflow requires a complex graph structure even for simple arithmetic operations. Why is that? It is because Tensorflow requires differential equations when performing an algorithm called gradient descent. The graph structure is a means to conveniently derive the differential equations. I explained why mathematically.

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

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.

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.

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