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An Introduction to Practical Deep Learning

An Introduction to Practical Deep Learning

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8.5/10 (Our Score)
Product is rated as #144 in category Machine Learning

This course provides an introduction to Deep Learning, a field that aims to harness the enormous amounts of data that we are surrounded by with artificial neural networks, allowing for the development of self–driving cars, speech interfaces, genomic sequence analysis and algorithmic trading. You will explore important concepts in Deep Learning, train deep networks using Intel Nervana Neon, apply Deep Learning to various applications and explore new and emerging Deep Learning topics. The Intel® Developer Zone offers tools and how–to information to enable cross–platform app development through platform and technology information, code samples, and peer expertise in order to help developers innovate and succeed. Join communities for the Internet of Things, Artificial Intelligence, Virtual Reality, Persistent Memory & Game Dev to download tools, access dev kits, share ideas with like–minded developers, and participate in hackathons, contests, roadshows, and local events.

Instructor Details

Andres Rodriguez is a Sr. Principal Engineer working with the Intel's Data Center Group (DCG) where he designs deep learning solutions for Intel’s customers and provides technical leadership across Intel for deep learning products. He has 13 years of experience working in artificial intelligence. Andres received his PhD from Carnegie Mellon University for his research in machine learning, and prior to joining Intel, he was a DL research scientist with the Air Force Research Laboratory and adjunct professor at Wright State University. He holds over 20 peer reviewed publications in journals and conferences, and a book chapter on machine learning.

Specification: An Introduction to Practical Deep Learning

Duration 12 hours
Year 2018
Level Intermediate
Certificate Yes
Quizzes Yes

16 reviews for An Introduction to Practical Deep Learning

4.1 out of 5
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  1. Avatar

    Brad C

    Love this course!! Thanks.

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  2. Avatar

    Dongliang Y

    Great course

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  3. Avatar

    Emil L

    A very dense and informative course.

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  4. Avatar

    Shubham r

    Good for theory knowledge , but very low in practical knowledge

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  5. Avatar

    Ehtesham H

    Excellent learning experience. Thank you…

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  6. Avatar

    Mohammed S E

    well it has been a good course for me to get an overall view on Deep learning , but there was so much information in every video that was hard to grasp from the first time

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  7. Avatar

    Ambar R

    very good

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  8. Avatar

    RAMA R R

    Thank you Intel and Coursera

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  9. Avatar

    Ramakrishna B C

    This course is not worth the time and money. I would suggest doing any of courses in the Andrew Ng’s deeplearning.ai specialization instead. No programming assignments that’s evaluated here. No instructor or TA are active in the forums. No questions are answered in the discussion forums. Many courses in deep learning are available online where you can actually learn something by getting hands on.

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  10. Avatar

    Praveen k

    No projects! The knowledge level is good though.

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  11. Avatar

    Gunjan B

    Tough Enough To Remove Dust Of Time From Your Brain. Quizes Were Good Brain Exercise

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  12. Avatar

    Raveesh G

    The theoretical aspect is good for those aiming at basics but the neon exercises are average. The data sets should be readily imported or there should at least be one standard method to import any kind of data set. Except for this part, the exercises complemented the videos.

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  13. Avatar

    Anirban L

    Awesome experience

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    B B B

    Very good course with practical aspects

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  15. Avatar

    Aditya B

    I thank Coursera and the instructors for guiding through the basics of Deep Learning. The explanations were easy to understand, and would recommend this course to enthusiasts.

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  16. Avatar

    Robert G

    Exercises do not work. Nervana is deprecated.

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    An Introduction to Practical Deep Learning
    An Introduction to Practical Deep Learning

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