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Virtual course of:Coursera |
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MAIN CATEGORY(S) OF THIS COURSE
ABOUT THIS COURSE
Machine learning is the science of making computers act without being explicitly programmed. In the last decade, machine learning has given us self-driving cars, practical voice recognition, effective web searching, 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 that it is the best way to move towards human-level AI. In this class, you'll learn about the most effective machine learning techniques, and get practice implementing them and making them work for yourself. Most importantly, you'll learn not only the theoretical underpinnings of learning, but you'll also gain the practical knowledge needed to quickly and powerfully apply these techniques to new problems. Finally you'
DESCRIPTION
This course provides a broad introduction to machine learning, data mining, 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 be based on numerous case studies and applications, so you will also learn how to apply learning algorithms to build intelligent robots (perception, control), text comprehension (web search, anti-spam), computer vision, medical informatics. , audio, database mining and other areas.
CHARACTERISTICS OF THIS COURSE
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Course language:English with English subtitles
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Created by:Stanford University
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Data science, business and personal development. You can enroll in multiple courses at once, earn unlimited certificates, and learn in-demand job skills to start, grow, and even change careers.
DISCOVER HOW TO GET THE MOST, AND SAVE OVER USD $500 WITH AN ANNUAL SUBSCRIPTION TO COURSERA PLUS*
*You save up to USD$500 in 12 months, when you go from paying USD$59 for a monthly subscription, to an annual subscription with the promotion. The normal annual subscription is USD $399. With the promotion you will only pay USD $299. Find out everything by clicking the yellow button.
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Andrew Ng INSTRUCTOR DIRECTOR
CEO / Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; former Chief Scientist, Baidu and Founding Director of Google Brain
my person_add 3.512.632 student(s)
my computer 11 course(s)
FAQs
METHODOLOGY
LEVEL OF STUDY
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COOKING CLASS DETAILS
- DELIVERY SCHEDULE: Study at your own pace and availability
- VIDEO HOURS: 56
- STUDY TIME (est): approximately 4 to 5 months (with an average of 6 hours per week).
- ACCESS TIME Access to content after completing the course
KEY ASPECTS OF THIS STUDY
- Logistic regression
- artificial neural network
- Machine learning (ML) algorithms
- Machine learning
NEW
Ricardo Salcedo
July 6, 2021 at 12: 07 pmThis course is an amazing and extensive resource for machine learning, that isn't afraid to dive into the math behind machine learning. I thoroughly enjoyed all the intuitive explanations and examples given by the instructor. By focusing on the basics of ML, rather than a specific programming language or library, this course ensures that it remains relevant even years after its release. Overall, this course can be a bit challenging for some people, but it is certainly worth all the time spent on it.