Studying Generative Adversarial Networks (GANs)

References Lecture 13: Generative Models. CS231n: Convolutional Neural Networks for Visual Recognition. Spring 2017. [SLIDE][VIDEO] Generative Adversarial Nets. Goodfellow et al.. NIPS 2014. 2014. [LINK][arXiv] How to Train a GAN? Tips and tricks to make GANs work. Soumith Chintala. github. [LINK] The GAN Zoo. Avinash Hindupur. github. [LINK]

Convolutional Neural Networks | Study

  References L. Fei-Fei, Justin Johnson (Spring 2017)CS231n: Convolutional Neural Networks for Visual Recognition. [LINK] Jefkine (5 September 2016). Backpropagation In Convolutional Neural Networks. [LINK] Convnet: Implementing Convolution Layer with Numpy [LINK] CNN의 역전파(backpropagation) [LINK]

Studying Tensorflow

References Géron, A. (2017). Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. O’Reilly Media [Amazon] Siraj Raval (2016. 8. 19.). TensorFlow in 5 Minutes. YouTube. [YouTube] TensorBoard: 그래프 시각화 [LINK] Cifar-10 CNN implementation using TensorFlow library with 24% error [GitHub] Terms of Tensorflow Variable ≠constant Session Placeholder Objects […]

Studying ‘Cognitive Science’

References Cognitive Science | Stanford Encyclopedia of Philosophy Suilin Lavelle, Kenny Smith, Mark Sprevak, David Carmel, Andy Clark & Barbara Webb (Mar. 2017) Philosophy and the Sciences: Introduction to the Philosophy of Cognitive Sciences. the University of Edinburgh. Coursera. 이정모. (2009). 인지과학: 학문 간 융합의 원리와 응용. 서울: 성균관대학교출판부. 이정모. (2010). 인지과학: 과거-현재-미래. 서울: 학지사. 장병탁, […]

Studying ‘Deep Learning’

References Lectures Hinton, G. (2013) Neural Networks for Machine Learning. Coursera Deep Learning Nanodegree Foundations. Udacity CS231n: Convolutional Neural Networks for Visual Recognition. Stanford University CS224d: Deep Learning for Natural Language Processing. Stanford University CS 294-131: Special Topics in Deep Learning. UC Berkeley CS 294: Deep Reinforcement Learning, Spring 2017. UC Berkeley Vanhoucke, V.. Deep Learning. Udacity Books Goodfellow, […]

Studying ‘Linguistics’

Fields of Linguistics 구분1: 시간 공시언어학 Descriptive linguistic 어떤 한 순간의 언어 상태를 연구 통시언어학/역사언어학 Historical linguistics 시간에 따른 언어의 변화를 연구 구분2: 연구 대상 음성학 Phonetics 음성의 물리적 성질 음운론 Phonology 화자가 말할 때 심리적으로 구분하는 소리(음운) 형태론 Morphology 단어의 내부 구조 통사론 Syntax 문장의 내부 구조 의미론 Semantics 단어의 의미와 단어의 조합에 따른 의미 변화 화용론 Pragmatics 대화에서 화자의 […]

Studying ‘Differential Equations’

References Second order linear equations | Differential Equations | Khan Academy I learned this topic very easily through this material. I learned how to solve the second order linear homogeneous equations 3 types of the character equation and its general solutions how to solve the second order linear nonhomogeneous equations The method of undetermined coefficients Summary […]

Studying ‘Artificial Intelligence’

Study Procedure Find and understand overall sub-fields of the artificial intelligence References Artificial intelligence – Wikipedia, the free encyclopedia Introduction to the artificial intelligence Sub-fields of the Artificial Intelligence The fields of the AI can be classified by goals, approaches, and tools. Goals Deduction, reasoning, problem solving Knowledge representation Default reasoning and the qualification problem […]