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.
Este curso forma parte de Programa Especializado - Aprendizaje profundo
ofrecido por
Programa Especializado - Aprendizaje profundodeeplearning.aiAcerca de este Curso
612,309 vistas recientes
Resultados profesionales del estudiante
36%
comenzó una nueva carrera después de completar estos cursos
38%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
14%
consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 3 de 5 en
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 5 horas para completar
Inglés (English)
Subtítulos: Chino (tradicional), Chino (simplificado), Coreano, Turco (Turkish), Inglés (English), Español (Spanish)
Habilidades que obtendrás
Machine LearningDeep LearningInductive TransferMulti-Task Learning
Resultados profesionales del estudiante
36%
comenzó una nueva carrera después de completar estos cursos
38%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
14%
consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 3 de 5 en
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 5 horas para completar
Inglés (English)
Subtítulos: Chino (tradicional), Chino (simplificado), Coreano, Turco (Turkish), Inglés (English), Español (Spanish)
ofrecido por
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.
Programa - Qué aprenderás en este curso
2 horas para completar
ML Strategy (1)
2 horas para completar
13 videos (Total 100 minutos), 1 lectura, 1 cuestionario
13 videos
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
1 lectura
Machine Learning flight simulator2m
1 ejercicio de práctica
Bird recognition in the city of Peacetopia (case study)45m
3 horas para completar
ML Strategy (2)
3 horas para completar
11 videos (Total 132 minutos)
11 videos
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
1 ejercicio de práctica
Autonomous driving (case study)45m
Revisiones
Principales revisiones sobre STRUCTURING MACHINE LEARNING PROJECTS
por EK27 de dic. de 2017
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
por AM22 de nov. de 2017
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.
por JB1 de jul. de 2020
While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).
por MG30 de mar. de 2020
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.
Acerca de Programa especializado: Aprendizaje profundo
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.
Preguntas Frecuentes
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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