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Volver a Aprendizaje Automático

Aprendizaje Automático, Universidad de Stanford

4.9
93,527 calificaciones
23,688 revisiones

Acerca de este Curso

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas....

Principales revisiones

por EJ

Mar 27, 2018

Very well structured and delivered course. Progressive introduction of concepts and intuitive description by Andrew really give a sense of understanding even for the more complex area of the training.

por MN

Jun 15, 2016

Excellent starting course on machine learning. Beats any of the so called programming books on ML. Highly recommend this as a starting point for anyone wishing to be a ML programmer or data scientist.

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22,845 revisiones

por Amit Giri

Feb 17, 2019

A nice course for enthusiastic programmer. Being a mechanical engineer, it is really helpful for me to know about the recent technologies used in the industry.

por sangyoon lee

Feb 17, 2019

Perfect course for ML beginner

por TAKASHI SEKIGUCHI

Feb 17, 2019

講師の方のわかりやすい講義・適度な課題の難易度

つまずくことは何度あったが何度も講義を見直すことで理解できるようになった。

本当に良い授業でした

por Allioux yann

Feb 16, 2019

Just perfect ! One of my best teacher !

por Henry Wu

Feb 16, 2019

Andrew Ng does a wonderful job demystifying ML for me. The course quizzes, programming assignments, slides, and videos all tied very well together.

por Denis OSullivan

Feb 16, 2019

Great introduction to Machine Learning.

It gave me exactly what I was hoping for: at the end of the course, I feel like I can look at a typical machine-learning / AI / neural network program and understand how it might work (of course, a specific program mightn#t work that way, but I#d know one way that it could work, and the type of results, predictions and flaws to expect.

The programming exercises were very helpful because they forces us to think and to refresh our knowledge of linear algebra. I would probably have made them a little bit harder - not that they were easy for me at all !!! - in the sense of ensuring that we had to always program the critical code for the key topic of a given lesson. But maybe that#s not realistic.

The lecturer is phenomenal - very clear, very precise, very engaging.

por Alain Berrier

Feb 16, 2019

Incredible course that explain me all the basics I needed to know about ML.

por Varun

Feb 16, 2019

This was my very first course on machine learning. Though I got very less time in my daily routine, but I always got attracted to it and wanted to know more about the upcoming topics. Thank you Andre Ng for delivering such an elaborate course.

por Aaron Sanders

Feb 16, 2019

Absolutely amazing course in the low-level details of machine learning algorithms and the overall concepts for designing machine learning systems. If you want to really understand what the algorithms you're using are doing and how to choose, design and improve them, this course is a great resource.

por Russell John Ramos Micumao

Feb 16, 2019

I love it. So easy to understand!