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 course will show you how.
제공자:
심층 학습 특화 과정deeplearning.ai이 강좌에 대하여
최근 조회 634,925회
학습자 경력 결과
36%
가 이 강좌를 수료한 후 새로운 커리어를 시작함
38%
가 이 강좌를 통해 확실한 경력상 이점을 얻음
14%
가 급여 인상 또는 승진 성취
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 5개 강좌 중 3번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
초급 단계
완료하는 데 약 5시간 필요
영어
자막: 중국어 (번체자), 중국어 (간체자), 한국어, 터키어, 영어, 스페인어
귀하가 습득할 기술
Machine LearningDeep LearningInductive TransferMulti-Task Learning
학습자 경력 결과
36%
가 이 강좌를 수료한 후 새로운 커리어를 시작함
38%
가 이 강좌를 통해 확실한 경력상 이점을 얻음
14%
가 급여 인상 또는 승진 성취
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 5개 강좌 중 3번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
초급 단계
완료하는 데 약 5시간 필요
영어
자막: 중국어 (번체자), 중국어 (간체자), 한국어, 터키어, 영어, 스페인어
제공자:
deeplearning.ai
Founded by Andrew Ng, deeplearning.ai is on a mission to make world-class AI education accessible to people around the globe so that we can all benefit from an AI-powered future.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 2시간 필요
ML Strategy (1)
완료하는 데 2시간 필요
13개 동영상 (총 100분), 1 개의 읽기 자료, 1 개의 테스트
13개의 동영상
Orthogonalization10m
Single number evaluation metric7m
Satisficing and Optimizing metric5m
Train/dev/test distributions6m
Size of the dev and test sets5m
When to change dev/test sets and metrics11m
Why human-level performance?5m
Avoidable bias6m
Understanding human-level performance11m
Surpassing human-level performance6m
Improving your model performance4m
Andrej Karpathy interview15m
1개의 읽기 자료
Machine Learning flight simulator2m
1개 연습문제
Bird recognition in the city of Peacetopia (case study)45m
완료하는 데 3시간 필요
ML Strategy (2)
완료하는 데 3시간 필요
11개 동영상 (총 132분)
11개의 동영상
Cleaning up incorrectly labeled data13m
Build your first system quickly, then iterate6m
Training and testing on different distributions10m
Bias and Variance with mismatched data distributions18m
Addressing data mismatch10m
Transfer learning11m
Multi-task learning12m
What is end-to-end deep learning?11m
Whether to use end-to-end deep learning10m
Ruslan Salakhutdinov interview17m
1개 연습문제
Autonomous driving (case study)45m
검토
STRUCTURING MACHINE LEARNING PROJECTS의 최상위 리뷰
EK 제공2017년 12월 27일
Loved the course, and the simulation was great. Doing an actual transfer learning programming exercise in TensorFlow could be an awesome addition. Best & thanks again for an awesome course!\n\nEric
MG 제공2020년 3월 30일
It is very nice to have a very experienced deep learning practitioner showing you the "magic" of making DNN works. That is usually passed from Professor to graduate student, but is available here now.
AM 제공2017년 11월 22일
I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.
WG 제공2019년 3월 18일
Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.
심층 학습 특화 과정 정보
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning.
In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.
You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice.
AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work.
We will help you master Deep Learning, understand how to apply it, and build a career in AI.
자주 묻는 질문
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
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