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Machine Learning With Big Data

Machine Learning With Big Data

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8.3/10 (Our Score)
Product is rated as #35 in category Big Data

Want to make sense of the volumes of data you have collected? Need to incorporate data–driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems. At the end of the course, you will be able to: – Design an approach to leverage data using the steps in the machine learning process. – Apply machine learning techniques to explore and prepare data for modeling. – Identify the type of machine learning problem in order to apply the appropriate set of techniques. – Construct models that learn from data using widely available open source tools. – Analyze big data problems using scalable machine learning algorithms on Spark. Software Requirements: Cloudera VM, KNIME, Spark UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn’t just acquired in the classroom—life is their laboratory.

Instructor Details

Mai H. Nguyen is the Lead for Data Analytics at the San Diego Supercomputer Center (SDSC) of the University of California, San Diego (UCSD). Her research centers on applying machine learning techniques to various scientific problems and combining machine learning methods with distributed computing to analyze large-scale data. Prior to joining SDSC, she worked in industry on applications in machine learning, data mining, business intelligence, and data warehousing. She has also been teaching in these areas since 2009. Mai received her M.S. and Ph.D. degrees in Computer Science from UCSD, with focus on machine learning.

Specification: Machine Learning With Big Data

Duration

16 hours

Year

2016

Certificate

Yes

Quizzes

No

56 reviews for Machine Learning With Big Data

4.3 out of 5
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  1. Nur K

    This is good courses, the explanation of the concept is easy to understand. Thank you!

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  2. Laurent C S

    great course, all examples with Spark and Knime were working for me

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  3. Emilio M

    Excellent, very useful

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  4. Rahul P

    The Hands On exercises were good. The theory part was too shallow.

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  5. Shin Y

    This course is quite good and easy to follow

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  6. Siva P R

    Good one !!

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  7. Rubiel V

    Fantastico!!!!

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  8. jauhar m

    This course help me to understand the missing point of my learning about Machine Learning. Since my background is not related with statistic, but the module and also the trainer help to understand easily of ML algorithm. Thanks for Ms Mai and Ilkay and someone who teach onhands on.

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  9. Eduard A L

    Excellent Course!

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  10. Jose R Z

    The concepts in the course are very good but very basics in machine learning, it’s a good introduction to knime and spark

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  11. Armando P

    Very well thought out and just enough content to intrigue the learner to continue digging.

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  12. Juan D P

    Awesome course.

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  13. Ivan M H C

    Excellent course.

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  14. Veronica Y G Z

    Esta Bien, 🙂

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  15. HUBER H M

    Thas good course for learn the machine learning and big data

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  16. Sun W

    Generally its good content. However the VM setup is still horrible. Many time wasted on debugging and set up environment.

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  17. Suraj J W

    Thanks for craeting such nice course and helping other to learn new technology

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  18. William J C

    Excellent course!!!! I learned a lot. The course structure, topics, explanations and activities were very precise. Thanks to the tutors.

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  19. ablewly

    great for learning ML

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  20. Ramalingaraju G

    great experience and learned about Machine Learning with Big Data

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  21. Somnath P

    It was a really nice experience to learn on the Machine Learning Platform. Cleared on Data Exploration, Classification, Regression and much more. Hands on exercises are very much interesting. Training Videos are nice and very well explained by the instructor with a good number of examples. Happy Machine Learning!

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  22. LOKESH R

    Very good

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  23. MINKI A

    Excellent course, I highly recommend

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  24. Amin O

    Awesome!! It would be great if more hands on (specially spark) will be added.

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  25. Victor R T C

    Excelente curso

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  26. MARTIN C

    Excellent Course. I would consider changing Spark for other similar to knime

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  27. SANJU M

    Excellent

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  28. Kamalesh P

    Regression is least bothered, less hands on

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  29. Doppalapudi P V S

    Ease of learning and visually attractive.

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  30. Jae Y S

    it was very useful for me to get knowledge about Machine Learning with somehow details and reminded me wh

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  31. Harshith

    It was brief and comprehensive , Got to learn various technologies like Knime and Spark

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  32. Mohamad K

    Its a great course! that provide you with many concepts of Machine learning. But Since this course is about big data and not about Machine learning, you have keep in the mind the concepts of deep learning. Because after training the data the you feed it to deep learning so that you discover more hidden patterns or to learn more about those patterns to predict unseen patterns.

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  33. Juan C C C

    Clearly explained course with practical hands on and insightful concepts.

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  34. Ayush A

    Good course to have a first hand and concise knowledge about various machine learning algorithms

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  35. Bharti G

    Excellent Course.

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  36. Amit M

    Extremely good. Lot of learning and course is very well designed and simple to understand. Thanks a lot for such courses.

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  37. David P G

    The didactic qualities of the lecturer greatly compensate the lack of support and maintenance.

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  38. Chandrakanth B

    Wonder full information i could able to learn, in this module it has been shown how ML is helps or used in to Big data area.

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  39. Suriya B

    Good

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  40. Ravisankar S

    Only one concern that was faced during the course is, unfortunately, all the needed spark related libraries are not available to setup. It would have been nice, if either online compilers or readily accessible along with the course, would have become learners journey smooth.

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  41. Francisco J H A

    The last week in my point of view is not linked to machine learning.

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  42. Tariq A

    The fact that the assignments are graded means that there’s incentive to work on them, solve problems, and ask questions. Traditional online courses don’t offer that incentive.

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  43. NAHUM I G A

    excelente curso

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  44. Miguel A R B

    There was a good explanation of concepts, but I think it was possible to include more themes or empathize more in other techniques.

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  45. Dev A S

    The instructor is explaining well. But still in some weeks there is a gap between the Hands on and theories

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  46. Angel M

    great!

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  47. JUAN P G B

    I am really thankful to help to start understand the machine learning in big data analysis field

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  48. Ripunjay K

    Needed more clear instructions in each module else a very good course to understand ML

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  49. Yomin E J M

    congratulations, it’s amazing

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  50. CRISTIAN A U R

    I highly recommend this course. Well explained, simple but complete enough to capture the basics of machine learning applied to big data analysis. It also has a good balance between theory and practice.

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  51. Basil C

    This has given me foundational knowledge in Machine Learning for someone who is not a practitioner. Thank you Mai Nguyen for the excellent course presentation. Keep it up.

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  52. Ahmed R

    I will surely recommend to others about this course. This built my basic pillars of Machine Learning. Thanks Coursera.

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  53. Gary T

    Good introduction

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  54. Ahmed M S

    This course is really nice and interesting one. Dr. Mai is excellent instructor and has good capabilities to simplify complex ideas. However, I did disagree with the course name since a main subject of this course “big data” is not touched in the given sample dataset.

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  55. Dhananjai P

    Good

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  56. Julian A A M

    Very good course, with a excelent generalization of all cases to use it in the real life.

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