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Art and Science of Machine Learning

Art and Science of Machine Learning

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8.1/10 (Our Score)
Product is rated as #250 in category Machine Learning

Welcome to the art and science of machine learning. In this data science course you will learn the essential skills of ML intuition, good judgment and experimentation to finely tune and optimize your ML models for the best performance. In this course you will learn the many knobs and levers involved in training a model. You will first manually adjust them to see their effects on model performance. Once familiar with the knobs and levers, otherwise known as hyperparameters, you will learn how to tune them in an automatic way using Cloud Machine Learning Engine on Google Cloud Platform.

Instructor Details

The Google Cloud Training team is responsible for developing, delivering and evaluating training that enables our enterprise customers and partners to use our products and solution offerings in an effective and impactful way. Google Cloud helps millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.

Specification: Art and Science of Machine Learning

Duration

8 hours

Year

2018

Level

Intermediate

Certificate

Yes

Quizzes

No

52 reviews for Art and Science of Machine Learning

3.8 out of 5
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  1. Raja R G

    Very very informative for learning….had good time to gothrough this course…

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  2. Morris C

    Thank you for such wonderful classes, it helps me a lot on tensorflow learning.

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  3. Pawan K T

    Great inside about the core topics with real word problems which make learning easier and practical. Thanks a lot for this great course

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  4. Joel M

    good lessons and in depth coverage of a range of issues

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  5. Attila B

    Really good course with a lot of practical examples.

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  6. Mark B

    thanks for the great work. There is so much to learn and I appreciate the effort you made to break things down and providing lab while making the hard decisions on what to commit.

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  7. Luciano M

    Labs were had less quality than in previous weeks.

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  8. Mario R

    Great course! You get some basics on how to fine tune your model (and why those methods are effective). Nice introduction to NN and what I think was the most relevant: building estimators from scratch and how Keras can offer a simpler way to work.

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  9. Muyide I

    Its one of the best course for machine learning

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  10. Richard K

    This was the most useful course in the specialisation.

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  11. Aman K S

    GREAT MENTORS with GREAT LEARNING EXPERIENCE

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  12. Alan I S R

    Excelente curso, muchas gracias!!

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  13. Putcha L N R

    Amazing way to keep the audience interested. Throughout the specialization, I was always interested to learn what was about to come, next up. I completely recommend this specialization. It is a fun way to learn!!

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  14. Eric

    It has a lot fo great content, but the way it’s laid out confused me greatly. It also felt very rushed at times, many parts weren’t explained in detail, making many parts much less educational than I feel they should’ve been. The best parts are where Lak is presenting, even in the lab solutions he went to more details than anyone else and made even those videos interesting after solving it myself.

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  15. Chingiz K

    Very interesting course! Specifically the last modules with custom estimators and the ability to create estimators straight from Keras!

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  16. Gennady L

    Thank you for this course and specialization, it really good. There were some small bumps in the labs, but those were minor. Appreciate the work you’ve done to put out this course and the specialization!

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  17. Swaraj P

    Nice tutorial

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  18. Harm t M

    Wow, really enjoyed parts of this one. Thanks

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  19. Arman A

    Pros: Tensorflow is an excellent framework for deep learning Cons : 1 The way this material is designed is 10 X SHIT 2 Either teach properly or don’t teach at all.

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  20. Muhammad A

    Great Course, i have learn alot

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  21. Rahul K

    Some tough concepts !!!

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  22. Dmitry B

    The quality of the lesson material is great but the quantity is nowhere sufficient to get the hands on experience

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  23. Raghuram N

    An advanced course with good techniques.

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  24. Fathima j

    good

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  25. Yakup K Y

    Some lab contents are distracting from the core subject, deviate from the video contents.

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  26. Mike W

    The notebook based demos are unfortunately pretty useless as labs. All of these courses would be much improved with real labs that require the student to build the system.

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  27. yu m c

    poor labs

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  28. Matthew B

    Labs were very confusing. Explained theories well but in practice didn’t really learn much. I wouldn’t recommend if you’re a beginner. Google has a very interesting way on teaching…. On that note they should stick to building tech, never teaching. Didn’t really learn how to build anything in ML, sort of skimmed on some API’s they offer. In reality, the first course was probably the best… The rest of the specialization was just a rinse and repeat sort of thing.

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  29. Jafed E

    I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

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  30. Nhan T N

    Great course for essential techniques in ML model design.

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  31. Manish G

    The course is quite good and have balance of theory and labs. It is useful course for beginners.

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  32. Ruslan A

    Many notebooks contain some typo/erros.

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  33. Naman M

    Awesome

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  34. Mr. J

    Now that’s what I am talking about. Great survey on nuts and bolts of ML practicalities. The how and why of model generation and manipulation. Very excellent. Super library of reference models and materials.

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  35. Manish K

    great

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  36. Ayush T

    This course is of specialization is the most applicable in the case of my work. If customer estimator was explained in the earlier courses, many other experiments with our own custom estimators could have been tried.

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  37. sumeyra d

    Advanced and detailed course for accurate tensorflow models

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  38. Mirza s n

    good

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  39. James W

    Good class with a lot of information and new terminology thrown at you. Especially if you don’t have a machine learning background. The labs are done in a way where you can get familiar with TensorFlow and Python programming, without having to know Python programming. Good intro if you want to be familiar with GCP ML. If you’re looking to write a bunch of code this will probably not be enough for you.

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  40. Pratik S

    complete hyper parameters is given in lab

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  41. Muhammad Z H

    Thanks Professor

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  42. Super–intelligent S o t C B

    Good course, but I couldn’t get over the Estimator API. IMHO it’s too complicated compared to Keras and I just could not force myself to care about it.

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  43. Super intelligent S o t C B

    Good course, but I couldn’t get over the Estimator API. IMHO it’s too complicated compared to Keras and I just could not force myself to care about it.

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  44. Mahendra S C

    Great course for understanding in and out of Machine learning model. I learn lots of cool thing in it. Most important I learn about Google Vizire: A great tool for hyper parameter tuning. Now I am starting “Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization”.

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  45. AMARTHALURU N K

    good

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  46. Akshay M

    Was a great experience with this course.

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  47. Mohan C

    Good one

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  48. Radha M K V

    Very redundant and superficial.

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  49. Cooper C

    My feeling is that this entire specialization is a glorified demonstration of what GCP can do with ML. The labs are not interactive and in some cases did not work. I don’t feel that I have learned anything new. If I were to use GCP for ML purposes, I would need additional training to do it. I don’t recommend this specialization

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  50. Fedric

    Excellent

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  51. GAURAV B

    I was looking for more hands on.

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  52. Fuat A

    Google provided with me an opportunity to take the specialization for free. Many thanks. Just a comment: Labs were great. But, it takes long when i needed to start a lab, i.e. Opening a Google account every time and starting a vm. So, it would be great if i could use the same vm for more than one lab assignment.

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