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: deeplearning.ai 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 […]

One-Shot Imitation Learning. Yan Duan et al. 2017

Summary Abstract Ideally, robots should be able to learn from very few demonstrations of any given task, and instantly generalize to new situations of the same task, without requiring task-specific engineering. In this paper, we propose a meta-learning framework for achieving such capability, which we call one-shot imitation learning. Task examples: to stack all blocks […]

Structuring Machine Learning Projects | Deep Learning Specialization | Coursera

Brief information Course name: Structuring Machine Learning Projects Instructor: Andrew Ng Institution: deeplearning.ai 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 […]

Samsung Notebook 9 Pen NT940X3M-K716S

모델 정보 출시연월: 2017년 9월 나의 제품 만든 연월: 2017년 12월 화면크기: 13.3 inch 가격비교 삼성 노트북9 Pen NT940X3M-K716S | 에누리 가격비교 리뷰 동영상 갤럭시 노트의 장점을 합친 최신 2in1 PC 삼성 노트북 9 펜(Pen) [LINK] Samsung NoteBook 9 Pen 15인치, 13.3인치 모델 배터리 구동 테스트 [LINK] 13.3인치: 10시간 50분 S펜을 품은 삼성의 플래그십 노트북, […]

HP Spectre x360

Official resources Software and driver results for: HP Spectre 13-ac000 x360 Convertible PC [LINK] 설치/설정 HP Notebook PCs – Updating the BIOS [LINK] 윈도우10 노트북 덮어도 안꺼지게 설정하는 방법, 절전모드 해제하기 [LINK] HP 스펙터 x360: 터치패드를 프리시전으로 만들기 [LINK] HP 스펙터 x360: 발열 문제 해결 방법 [LINK] Battery drain problem 노트북 배터리 자연 방전 | HP […]

Conditional Generative Adversarial Nets | M. Mirza, S. Osindero | 2014

Introduction Conditional version of Generative Adversarial Nets (GAN) where both generator and discriminator are conditioned on some data y (class label or data from some other modality). Architecture Feed y into both the generator and discriminator as additional input layers such that y and input are combined in a joint hidden representation.

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]

Lecture 2: Markov Decision Processes | Reinforcement Learning | David Silver | Course

1. Markov Process / Markov chain 1.1. Markov process A Markov process or Markov chain is a tuple such that is a finite set of states, and is a transition probability matrix. In a  Markov process, the initial state should be given. How do we choose the initial state is not a role of the Markov process. 1.2. State […]