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Mark Kim

더 많은 분들이 머신 러닝과 딥러닝에 대해 더 이해하고 본인들의 문제를 이 멋진 도구를 이용해서 풀수 있게 하기위해 비디오 강의를 준비하였습니다. 더 나아가 이론에만 그치지 않고 최근 구글이 공개한 머신러닝을 위한 오픈소스인 TensorFlow를 이용해서 이론을 구현해 볼수 있도록 하였습니다.

Sung Kim

모두를 위한 딥러닝 - 기본적인 머신러닝과 딥러닝 강좌

We have prepared video lectures so that more people can understand machine learning and deep learning and solve their own problems using these great tools. Furthermore, we have not only covered the theory, but also implemented the theory using TensorFlow, an open source for machine learning recently released by Google.

입문

초급

중급이상

Deep Learning(DL)

Reinforcement Learning(RL)

Deep Learning for Everyone - Basic Machine Learning and Deep Learning Course

Orientation

Machine Learning Concepts and Terminology

Concept of Linear Regression

Minimize the Linear Regression cost function

Linear Regression of Multiple Inputs (Features)

Logistic (Regression) Classification

Softmax Regression (Multinomial Logistic Regression)

ML in action and some tips

Basic concepts, problems, and solutions of deep learning

Neural Network 1: XOR problem and learning method, Backpropagation

Neural Network 2: ReLU and Initialization (2006/2007 breakthrough)

Convolutional Neural Networks

Recurrent Neural Network

Deep Deep Network Running with GPU on AWS (powered bt AWS)

Use Spot Instances in AWS at low cost without worrying about termination

Running TensorFlow with Google Cloud ML