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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.’

haesunpark

Do It! Introduction to Deep Learning

입문

초급

중급이상

Deep Learning(DL)

Machine Learning(ML)

Artificial Neural Network

Chapter 1: Introducing Deep Learning

Chapter 2 Minimal Tools for Deep Learning

Chapter 3: Establishing Machine Learning Basics - Numerical Prediction

Chapter 4 Building a neuron that classifies - Binary classification

Chapter 5 Learning Training Know-How

Chapter 6 Connecting Two Layers - Multilayer Neural Network

Chapter 7 Classifying Multiple Items - Multiclass Classification

Chapter 8 Classifying images - Convolutional Neural Networks

Chapter 9: Classifying Text - Recurrent Neural Networks