Deep learning Basic by Andrew Ng

• • Computer Vision 학습에 대한 전반적인 내용을 기재

  • 출처 : Andrew Ng open 강의, 자막: 커넥트재단

  • 1. 신경망과 딥러닝

    • https://www.edwith.org/deeplearningai1

  • 2. 심층 신경망 성능 향상키시기

    • https://www.edwith.org/deeplearningai2

  • 3. 머신러닝 프로젝트 구조화하기

    • https://www.edwith.org/deeplearningai3

  • 4. 합성곱 신경망 네트워크 (CNN)

    • https://www.edwith.org/deeplearningai4

※ 저작권 등의 문제로 링크만 첨부합니다.

CS 231n - 2017 in Stanford

• • Computer Vision 학습에 대한 전반적인 내용을 기재

  • 출처 : Stanford University School of Engineering

  • 강의 목차

    • Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition

    • Lecture 2 | Image Classification

    • Lecture 3 | Loss Functions and Optimization

    • Lecture 4 | Introduction to Neural Networks

    • Lecture 5 | Convolutional Neural Networks

    • Lecture 6 | Training Neural Networks I

    • Lecture 7 | Training Neural Networks II

    • Lecture 8 | Deep Learning Software

    • Lecture 9 | CNN Architectures

    • Lecture 10 | Recurrent Neural Networks

    • Lecture 11 | Detection and Segmentation

    • Lecture 12 | Visualizing and Understanding

    • Lecture 13 | Generative Models

    • Lecture 14 | Deep Reinforcement Learning

    • Lecture 15 | Efficient Methods and Hardware for Deep Learning

    • Lecture 16 | Adversarial Examples and Adversarial Training

※ 저작권 등의 문제로 링크만 첨부합니다.

자막 Link : https://github.com/insurgent92/CS231N_17_KOR_SUB

Etc..

Pocket Cluster : Deep Learning Trend

• • 링크 : https://blog.pocketcluster.io/