Seminar in Methodology on Experimental Psychology (Fundamentals and Applications of Cognitive Modeling) | MS in CogSci

Brief Information Name (en) : Seminar in Methodology on Experimental Psychology (Fundamentals and Applications of Cognitive Modeling) Name (ko) : 실험심리방법론세미나 (인지모델링의 기초와 응용) Lecturer : Koh, Sungryong 고성룡 Semester : 2018 Fall Major : MS, Cognitive Science Textbook Busemeyer, J. R., & Diederich, A. (2010). Cognitive modeling. Sage. Syllabus : 2018-2_Seminar-in-Methodology-on-Experimental-Psychology.pdf In short To learn cognitive modeling and its […]

Sequence Modeling | Deep Learning Specialization | Coursera

Course planning Week 1: Recurrent neural networks Learn about recurrent neural networks. This type of model has been proven to perform extremely well on temporal data. It has several variants including LSTMs, GRUs and Bidirectional RNNs, which you are going to learn about in this section. Lectures: Recurrent neural networks C4W1L01 Why sequence models C4W1L02 […]

Convolutional Neural Networks | Deep Learning Specialization | Coursera

Course Planning Week 1: Foundations of convolutional neural networks Learn to implement the foundational layers of CNNs (pooling, convolutions) and to stack them properly in a deep network to solve multi-class image classification problems. Convolutional neural networks C4W1L01 Computer vision C4W1L02 Edge detection example C4W1L03 More edge detection C4W1L04 Padding C4W1L05 Strided convolutions C4W1L06 Convolutions over […]

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization | Deep Learning Specialization | Coursera

Brief information Course name: Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization Instructor: Andrew Ng Institution: Media: Coursera Specialization: Deep Learning Duration: 3 weeks About this Course This course will teach you the “magic” of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand […]

Structuring Machine Learning Projects | Deep Learning Specialization | Coursera

Brief information Course name: Structuring Machine Learning Projects Instructor: Andrew Ng Institution: Media: Coursera Specialization: Deep Learning Duration: 2 weeks About this Course You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team’s work, this […]

CS231n: Convolutional Neural Networks for Visual Recognition | Course

Lecture 6 | Training Neural Networks I Sigmoid Problems of the sigmoid activation function Problem 1: Saturated neurons kill the gradients. Problem 2: Sigmoid outputs are not zero-centered. Suppose a given feed-forward neural network has hidden layers and all activation functions are sigmoid. Then, except the first layer, the other layers get only positive inputs. […]

Minds and Machines (24.09x) | edX

Brief Summary Course title: Minds and Machines [HOME] Platform: edX Duration: 15 weeks Instructors: Alex Byrne, Chair of Philosophy Section, MIT Ryan Doody, PhD in Philosophy & Linguistics, MIT Short summary of this course An introduction to philosophy of mind, exploring consciousness, reality, AI, and more. The most in-depth philosophy course available online. About this course What is […]

Computational Neuroscience | Course | MS CogSci

Range 8.1~8.7 9.1~9.10 10.1~10.14 10.19~10.21 Chapter 8. Principal-Components Analysis 8.1. Introduction Self-organized learning Self-organized learning is a type of unsupervised learning. locality of learning 8.2. Principles of Self-Organization Principle 1: self-amplification The following rule is based on Hebb’s postulate of learning. If two neurons of a synapse are activated simultaneously, then synaptic strength is selectively […]

Intro to Psychology | Udacity

Brief Information Instructors: Susan Snycerski (Assistant Professor, San Jose State University) Greg Feist (Professor, San Jose State University) Lauren Castellano (Udacity) Flatform: Udacity Course homepage:–ps001 Duration 2017-08-24~present: (blank) About this course Introduction to Psychology is a journey through all of the major psychological concepts and principles. The knowledge gained from this course will allow students to […]

Deep Learning | Udacity

Brief Information Instructor: Vincent Vanhoucke (Principal Scientist at Google Brain) Flatform: Udacity Course homepage:–ud730 Duration 2017-08-24~25: Took Lesson 1, 3-7 without programming assignments. Course Overview Lesson 1: From Machine Learning to Deep Learning Lesson 2: Assignment: notMNIST Lesson 3: Deep Neural Networks Lesson 4: Convolutional Neural Networks Lesson 5: Deep Models for Text and Sequences Lesson 6: […]