About this Course
최근 조회 9,416

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지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

초급 단계

완료하는 데 약 8시간 필요

권장: 9 hours/week...

영어

자막: 영어, 스페인어, 루마니아어

귀하가 습득할 기술

Artificial Intelligence (AI)Artificial Neural NetworkMachine LearningDeep Learning

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

초급 단계

완료하는 데 약 8시간 필요

권장: 9 hours/week...

영어

자막: 영어, 스페인어, 루마니아어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 1시간 필요

Deep Learning Products & Services

For the course “Deep Learning for Business,” the first module is “Deep Learning Products & Services,” which starts with the lecture “Future Industry Evolution & Artificial Intelligence” that explains past, current, and future industry evolutions and how DL (Deep Learning) and ML (Machine Learning) technology will be used in almost every aspect of future industry in the near future. The following lectures look into the hottest DL and ML products and services that are exciting the business world. First, the “Jeopardy!” winning versatile IBM Watson is introduced along with its DeepQA and AdaptWatson systems that use DL technology. Then the Amazon Echo and Echo Dot products are introduced along with the Alexa cloud based DL personal assistant that uses ASR (Automated Speech Recognition) and NLU (Natural Language Understanding) technology. The next lecture focuses on LettuceBot, which is a DL system that plants lettuce seeds with automatic fertilizer and herbicide nozzles control. Then the computer vision based DL blood cells analysis diagnostic system Athelas is introduced followed by the introduction of a classical and symphonic music composing DL system named AIVA (Artificial Intelligence Virtual Artist). As the last topic of module 1, the upcoming Apple watchOS 4 and the HomePod speaker that was presented at Apple's 2017 WWDC (World Wide Developers Conference) is introduced.

...
5 videos (Total 34 min), 2 quizzes
5개의 동영상
1.1 Future Industry Evolution & Artificial Intelligence11m
1.2 IBM Watson7m
1.3 Amazon Echo, Echo Dot, Alexa5m
1.4 LettuceBot / 1.5 Athelas / 1.6 AIVA (Artificial Intelligence Virtual Artist) / 1.7 Apple watchOS 4, HomePod speaker5m
2개 연습문제
Ungraded Quiz8m
Graded Quiz14m
2
완료하는 데 1시간 필요

Business with Deep Learning & Machine Learning

The second module “Business with Deep Learning & Machine Learning” first focuses on various business considerations based on changes to come due to DL (Deep Learning) and ML (Machine Learning) technology in the lecture “Business Considerations in the Machine Learning Era.” In the following lecture “Business Strategy with Machine Learning & Deep Learning” explains the changes that are needed to be more successful in business, and provides an example of business strategy modeling based on the three stages of preparation, business modeling, and model rechecking & adaptation. The next lecture “Why is Deep Learning Popular Now?” explains the changes in recent technology and support systems that enable the DL systems to perform with amazing speed, accuracy, and reliability. The last lecture “Characteristics of Businesses with DL & ML” first explains DL and ML based business characteristics based on data types, followed by DL & ML deployment options, the competitive landscape, and future opportunities are also introduced.

...
4 videos (Total 32 min), 2 quizzes
4개의 동영상
2.2 Business Strategy with Machine Learning & Deep Learning8m
2.3 Why is Deep Learning Popular Now?6m
2.4 Characteristics of Businesses with DL & ML7m
2개 연습문제
Ungraded Quiz8m
Graded Quiz20m
3
완료하는 데 1시간 필요

Deep Learning Computing Systems & Software

The third module “Deep Learning Computing Systems & Software” focuses on the most significant DL (Deep Learning) and ML (Machine Learning) systems and software. Except for the NVIDIA DGX-1, the introduced DL systems and software in this module are not for sale, and therefore, may not seem to be important for business at first glance. But in reality, the companies that created these systems and software are indeed the true leaders of the future DL and ML business era. Therefore, this module introduces the true state-of-the-art level of DL and ML technology. The first lecture introduces the most popular DL open source software TensorFlow, CNTK (Cognitive Toolkit), Keras, Caffe, Theano, and their characteristics. Due to their popularly, strong influence, and diverse capabilities, the following lectures introduce the details of Google TensorFlow and Microsoft CNTK. Next, NVIDIA’s supercomputer DGX-1, that has fully integrated customized DL hardware and software, is introduced. In the following lectures, the most interesting competition of human versus machine is introduced in the Google AlphaGo lecture, and in the ILSVRC (ImageNet Large Scale Visual Recognition Challenge) lecture, the results of competition between cutting edge DL systems is introduced and the winning performance for each year is compared.

...
4 videos (Total 28 min), 2 quizzes
4개의 동영상
3.3 Microsoft CNTK (Cognitive Toolkit) / 3.4 NVIDIA DGX-13m
3.5 Google AlphaGo8m
3.6 ILSVRC (ImageNet Large Scale Visual Recognition Challenge)8m
2개 연습문제
Ungraded Quiz8m
Graded Quiz20m
4
완료하는 데 1시간 필요

Basics of Deep Learning Neural Networks

The module “Basics of Deep Learning Neural Networks” first focuses on explaining the technical differences of AI (Artificial Intelligence), ML (Machine Learning), and DL (Deep Learning) in the first lecture titled “What is DL (Deep Learning) and ML (Machine Learning).” In addition, the characteristics of CPUs (Central Processing Units) and GPUs (Graphics Processing Units) used in DL as well as the representative computer performance units of FLOPS (FLoating-Point Operations Per Second) and IPS (Instructions Per Second) are introduced. Next, in the NN (Neural Network) lecture, the biological neuron (nerve cell) and its signal transfer is introduced followed by an ANN (Artificial Neural Network) model of a neuron based on a threshold logic unit and soft output activation functions is introduced. Then the extended NN technologies that uses MLP (Multi-Layer Perceptron), SoftMax, and AutoEncoder are explained. In the last lecture of the module, NN learning based on backpropagation is introduced along with the learning method types, which include supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning.

...
3 videos (Total 28 min), 2 quizzes
3개의 동영상
4.2 NN (Neural Network)7m
4.3 Neural Network Learning (Backpropagation)10m
2개 연습문제
Ungraded Quiz10m
Graded Quiz20m
4.3
74개의 리뷰Chevron Right

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Deep Learning for Business의 최상위 리뷰

대학: RNOct 2nd 2018

Amazing lectures! Detailed description of each topic coupled with mind blowing graded assignments! :)\n\nThanks a real bunch, Coursera for offering this courses & of course, scholarship!

대학: NAMar 3rd 2019

Even though I do not have the background of Computer Engineering or Science I was able to understand from the professor and the final project truly was able to explain everything for me.

강사

Avatar

Jong-Moon Chung

Professor, School of Electrical & Electronic Engineering
Director, Communications & Networking Laboratory

연세 대학교 정보

Yonsei University was established in 1885 and is the oldest private university in Korea. Yonsei’s main campus is situated minutes away from the economic, political, and cultural centers of Seoul’s metropolitan downtown. Yonsei has 3,500 eminent faculty members who are conducting cutting-edge research across all academic disciplines. There are 18 graduate schools, 22 colleges and 133 subsidiary institutions hosting a selective pool of students from around the world. Yonsei is proud of its history and reputation as a leading institution of higher education and research in Asia....

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 수료증을 구매하면 성적 평가 과제를 포함한 모든 강좌 자료에 접근할 수 있습니다. 강좌를 완료하면 전자 수료증이 성취도 페이지에 추가되며, 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 콘텐츠만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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