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Advanced Machine Learning

$44.00

(4 customer reviews)
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This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision, and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses, you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings.

4 reviews for Advanced Machine Learning

  1. yevgen a

    Great course. Even though I’ve done Andrew Ng’s ML course twice and completed his Deep Learning Specialization, I learned a lot of new things in this Intro Course of AML specialization.

  2. dmitry

    Alexander Panin has ruined this course with his pronunciation

  3. lewis b

    Overall a very good course. Highly informative, and strikes a good balance of the application of neural networks and theoretical background. I should mention that I have studied mathematics to MSc level so I didn’t find the mathematical aspects of the course challenging but this is will vary depending on your own background – previous study of multivariate calculus will help a lot.

    I particularly enjoyed the tensorflow content and found this to be particularly well taught, in fact it is the best introduction that I have found for this module. Personally, I would like to have seen more of autoencoders and less of CNNs but this is probably due to my own individual area of application – time series are more relevant to me than computer vision – and it really is only a preference.

    Lastly, I believe if you are going to learn something it is worth learning it properly and comprehensively. This course does that and I doubt you will find a better introduction to neural networks in that respect.

  4. nikita f

    Most video lectures are useless, lecturers are just reading some text from a paper/screen, some of them have english very far away from perfect. Each programming assignment is more about struggling with bugs rather than learning something about ML. Final project is a torture for students without GPU, you spent 5 hours training the model – your final loss was too low. Can you add a test/assertion for the loss function?

    So far it was my worst coursera experience.

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