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Machine Learning Foundations: A Case Study Approach

Machine Learning Foundations: A Case Study Approach

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(59 customer reviews)
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9.0/10 (Our Score)
Product is rated as #44 in category Machine Learning

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands–on experience with machine learning from a series of practical case–studies. At the end of the first course you will have studied how to predict house prices based on house–level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands–on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of …

Instructor Details

Carlos Guestrin is the Amazon Professor of Machine Learning at the Computer Science & Engineering Department of the University of Washington. He is also a co-founder and CEO of Dato, Inc., focusing on making it easy to build intelligent applications that use large-scale machine learning at their core. His previous positions include the Finmeccanica Associate Professor at Carnegie Mellon University and senior researcher at the Intel Research Lab in Berkeley. Carlos is a recipient of a National Science Foundation CAREER Award, an Alfred P. Sloan Fellowship, and the Stanford Centennial Teaching Assistant Award. Carlos was also named one of the 2008 `Brilliant 10' by Popular Science Magazine, received the IJCAI Computers and Thought Award from the top AI conference, and the Presidential Early Career Award for Scientists and Engineers (PECASE) from President Obama.

Specification: Machine Learning Foundations: A Case Study Approach

Duration

24 hours

Year

2015

Certificate

Yes

Quizzes

Yes

59 reviews for Machine Learning Foundations: A Case Study Approach

4.4 out of 5
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  1. Ivo R

    This course is very frustrating because it uses a library called Turi Create that can’t be installed on Windows 10. There is no support on how to setup you local environment after three days of frustration I decided to cancel my subscription. When I opened the forum for week one all the threads were asking the same question: “How to install Turi Create on Windows 10.” It would have been much better if the course was done with a more popular library like Skit–learn. This course is useless if you don’t use a Linux or a Mac

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  2. Lagadic A

    Great course to get a big picture of what machine learning is, what the models involved are.

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  3. Hamid K

    Great course. Hope to see and update on using the libraries and facilitate the learning process for the students. Thanks,

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  4. Amar

    Nice lectures and weekly assignments, great place to work.

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  5. Sudhir P

    Awesome learning experience.. loved it:)

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  6. Om D

    Nice Course with Detailed explanation

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  7. SHAH H

    Enhance my knowledge in ML and skilled me to do best Research in my MS Study, Thanks to COURSERA and University of Washington to give financial aid to learn Machine Learning.

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  8. Chalapathi R K

    I learned fundamentals of Machine Learning. I enjoyed learning with good content of videos and do

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  9. Ramiro V S J

    Esta sendo sensacional o curso.

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  10. Marta C G

    The course was OK, but I would introduce more about scikit–learn rather than a library that can only be installed in MacOS or Linux in an easier way

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  11. George

    the course has been very helpful in my development in the field of data science

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  12. Priyanka D

    The course is very insightful and brilliantly covers all the basics of different techniques in an easy to understand and engaging manner.

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  13. Kishore S

    Lecturer explained the course very clearly and course designed really excellent

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  14. Deveer B

    Very good theory and practical approach. However, some of the assignments are not very clear while explaining the questions due to which sometimes we get wrong results.

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  15. XingliangZhao

    To be honest, this course is not friendly to windows 10 users because it forces students to use the apple Inc’s Turicreate instead of the most popular sklearn. Admittedly, windows 10 users can still install the Turicreate by WSL but not everyone wants to add a subsystem to their windows just for this course. Except for this, this course has a nice structure and the content is really practice–oriented.

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  16. Mahajan P J

    The course was good.

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  17. Kelsey H

    Very frustrating. This course is a good Machine Learning overview, and light on programming. BUT the homework is based around an opensource library, TuriCreate – this is only available for Mac OS. Windows users will have a harder time with this course. The workaround I found was to register for a student version of GraphLab (which the course previously used). I used an older version of Anaconda that I got from the GraphLab website, and modified the homework assignments to use GraphLab instead of TuriCreate

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  18. Nick S

    The videos are great! The ourse is well structured and introduces gradually the complexity. Unfortunately, the exercises requires the use of a specific library, instead of scikit–learn and numpy. Although this library is a great pedagogic tool, it doesn’t work well with google colab and Jupyter notebook, especially when you need to display a graph or a picture. Because of this, I was not able to answer to few questions, and I to rely on my luck.

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  19. Enock A

    i loved the case study and hands on approach put to this course. really got me excited and eager about the next steps all through the course.

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  20. Prashanth B

    Great introductory course on different ML concepts.

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  21. aolei

    good

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  22. ARNAB N

    Very nice program

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  23. Matthew S

    A well rounded and not intimidating approach to machine learning. The concepts are introduced clearly and succinctly. The exercises are relevant and digestible. I feel like I have a much better understanding of the concepts to build upon. The only thing I would have liked to see is more outside reading on things that were introduced, but that’s also in the next courses of the specialization or just a google away.

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  24. Jane z

    I really enjoyed this hands–on course with a lot of practice. The difficult part was the week 1 when we had to set up the virtual environment, and pass the first quiz. I believe that if there is more support at the beginning, more people would have stayed on to finish the course. Thank you!

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  25. Borys B

    Easy to understand and learn ML thanks to this course. Thumbs up!

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  26. Chao T

    This course is great. I have a good understanding of Machine Learning concepts and algorithms during this studying period.

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  27. Bommareddy K r

    very useful for everyone how wants to learn machine learning

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  28. abhishek s

    instructor was awesome the way that explain was very easy

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  29. Jay G

    This course would have been better if the assignments were in python.

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  30. Raj K D

    Intense but at the same time fun learning

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  31. Mopuru V R

    Thank you

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  32. Jacob W

    Excellent course! Very well laid out and explained in simple terms!

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  33. Abdulrazak Z

    REAL–LIFE artificial intelligence applications. The examples were so good and real match to the reality, so in this course, I wasn’t bored by theoretical information but I have seen its benefits with the code I write.

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  34. Aleksei Z

    Materials from video differ from the web ( in videos graphlab, in materials Turicreat), including home assignment.

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  35. Rodrigo P d S

    Excelente!!!

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  36. Paul H

    Great overview of machine learning concepts. The content is structured in a helpful way to give you conceptual understanding of machine learning. Some of the quizzes and materials are a bit messy (most of the challenge is figuring out what parts are out of date or related to course material that previously existed). For the price, it’s definitely worth it.

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  37. Jose L C G

    Fantastic course, I learned a lot and very practical

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  38. Sarra Z

    I liked this course, it is really based on study cases approaches and covers many problematics in machine learning

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  39. Yunqi H

    Great intro class but very fun !

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  40. tanachote r

    Good style of teaching and modeling is very clear

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  41. Yuhuan Z

    Very good introduction to machine learning theory. The content is also very interesting.

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  42. Sunil N

    Updated videos in line with Turicreate could be of great help. Thoroughly enjoyed the learning experience though! Thanks to both the tutors!

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  43. Jawahir M A K

    It will give you an overview about the ML concept. But to get detail we need to have the specialization course or learn it our self.

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  44. Rahul R

    This course is awesome. One of the best course available in Coursera platform. I really appreciate both instructors’ hard–work. They are fun loving and enjoy teaching; at the same time they understand, how to make student listen and understand concepts. Both the instructors are really really awesome and genius as they explains every complex concept with simple explanation. Both of them reminds a quote by Albert Einstein –“The definition of genius is taking the complex and making it simple.”

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  45. UsmanIlamDin

    the Content was good,Instructor well explain. but at some point they need more explanation related to assignments and quize

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  46. Stefan v D

    A great foundational introduction to Machine learning concepts. Ideal for people that have some background in maths and programming but no career in this direction.

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  47. MOHD N B A L

    good

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  48. amit d

    nice explaination

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  49. Troy D

    Good course, learned a lot of basics. I think this course is rather old though and getting a lot of the required software up and running required a lot of work since there are much newer versions available now. I found that I had to do a little extra to get the older packages working in Jupiter.

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  50. Nsikan U

    Great overview and hands on introduction to ML concepts

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  51. Sarthak S

    This course is the best in this Specialization.

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  52. Arjun P

    A very good course that gave me a jump start to machine learning application and got me right into coding the applications. This course takes a very different approach to teaching ML and I guess it works as it keeps me interested and makes me want more from this course.

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  53. Bipin K C

    Awesome, This is what i liked pretty much in this course is that, learning by doing! This is what should be followed for most of the course.

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  54. Tairan Y

    A good approach to understand some basic machine learning methods as well as learn the fundamental Python practices. A good starting point for DS.

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  55. abdulkarim k

    Thanks Carlos and Emily very much for this wonderful course. Your way of presenting the topics is very cool 🙂

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  56. Ujwal A

    This course has used windows OS and application built for it. But the library/application is no longer supported on windows. So this is really a big problem for windows users.

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  57. Bhavesh G

    This course foundation for those who want to do specialization in Machine Learning. It’s really very useful course, I recommend do this course If you want to do specialization in Machine Learning.

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  58. lalith

    The concepts on recommendation systems could have been explain better. Having to use TuriCreate instead of open source libraries is a major drawback. Turicreate is also so high level its hard to understand whats happening under the hood. Everything else is great.

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  59. Peter F

    This course would be okay if it weren’t for turicreate, a Python package that’s supposed to simplify things. If you have Linux or a Mac, it will do just that, but if you have Windows steer well clear of this course. The lecturers haven’t considered the possibility that anyone might not have Linux or a Mac. All the faffing around getting turicreate to work (I did it once and I’m not doing it again) wasn’t worth my trouble so I ended up guessing the answers to the quiz questions (you’re allowed three attempts every eight hours) just to get this course out of the way. I’ll use something actually accessible for the remaining courses, namely R.

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    Machine Learning Foundations: A Case Study Approach
    Machine Learning Foundations: A Case Study Approach

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